ON-FARM PHENOTYPIC CHARACTERIZATION AND

PERFORMANCE EVALUATION OF BATI, BORENA AND SHORT

EARED SOMALI GOAT POPULATIONS OF ETHIOPIA

MSc THESIS

HULUNIM GATEW

MAY, 2014

HARAMAYA

ON-FARM PHENOTYIC CHARACTERIZATION AND

PERFORMANCE EVLUATION OF BATI, BORENA AND SHORT

EARED SOMALI GOAT POPULATIONS OF ETHIOPIA

A Thesis Submitted to the

School of Animal and Range Sciences, School of Graduate Studies

HARAMAYA UNIVERSITY

In Partial Fulfillment of the Requirements for the Degree of MASTER

OF SCIENCE IN AGRICULTURE (ANIMAL GENETICS AND

BREEDING)

By

Hulunim Gatew

March, 2014

Haramaya

ii

SCHOOL OF GRADUATE STUDIES

HARAMAYA UNIVERSITY

As Thesis Research advisors, we hereby certify that we have read and evaluated this thesis

prepared, under our guidance, by Hulunim Gatew entitled On-Farm Phenotypic

Characterization and Performance Evaluation of Bati, Borena and

Short-Eared Somali Goat Populations of Ethiopia. We recommend that it be

submitted as fulfilling the Thesis requirement.

Dr. HALIMA HASSEN ________________ _____________

Major Advisor Signature Date

Dr. KEFELEGN KEBEDE _________________ ___________

Co-advisor Signature Date

Dr. AYNALEM HAILE _________________ ___________

Co-advisor Signature Date

Dr. BARBARA ANN RISCHKOWSKY __________________ ___________

Co-advisor Signature Date

As member of the Board of Examiners of the M.Sc. Thesis Open Defense Examination,

We certify that we have read, evaluated the Thesis prepared by Hulunim Gatew, and

examined the candidate. We recommend that the Thesis be accepted as fulfilling the

Thesis requirement for the Degree of Master of Science in Agriculture (Animal Genetics

and Breeding).

Dr. Negassi Amha __________________ 17 May, 2014

Chairperson Signature Date

Prof. A.K. Banerjee _________________ 17 May, 2014

Internal Examiner Signature Date

Dr. Solomon Abegaz _________________ 17 May, 2014

External Examiner Signature Date

iii

DEDICATION

I dedicate this Thesis manuscript to my mother W/ro ASCHAL MEHARI, my father Ato

GATEW TARIKU and my lovely sister BEGOADRAGOT GATEW whom I lost when

I was first year of MSc student. BEGO GOD rest your soul in absolute peace.

iv

STATEMENT OF AUTHOR

First, I declare that this thesis is my bonafide work and that all sources of materials used

for this thesis have been duly acknowledged. This thesis has been submitted in partial

fulfillment of the requirements for MSc. degree at Haramaya University and is deposited

at the University Library to be made available to borrowers under rules of the Library. I

solemnly declare that this thesis is not submitted to any other institution anywhere for the

award of any academic degree, diploma, or certificate.

Brief quotations from this thesis are allowable without special permission provided that

accurate acknowledgement of source is made. Requests for permission for extended

quotation from or reproduction of this manuscript in whole or in part may be granted by

the head of the School of Animal and Range Science or the Dean of School of Graduate

Studies when in his or her judgment the proposed use of the material is in the interests of

scholarship. In all other instances, however, permission must be obtained from the author.

Name: Hulunim Gatew Signature:

Place: Haramaya University, Haramaya

Date of Submission: 26 May, 2014

v

BIOGRAPHICAL SKETCH

The author of this thesis, Mr. Hulunim Gatew, was born on July 23, 1985 at Machakel

District, East Gojjam Zone, Amhara Regional State, Ethiopia from his father Ato Gatew

Tariku and mother W/ro Aschal Mehari. He attended his primary education at

Medebebegn Elementary School; and his secondary education at Amanuel Senior

Secondary and Debre Markos Higher Education Preparatory Schools. He then joined

Haramaya University, College of Agriculture department of Animal Production in 2007

and awarded a B.Sc. degree in Agriculture (Animal Production) in July 2009.

Soon after graduation, the author was recruited by Ministry of Education at Debre Berhan

University in the Department of Animal Sciences, and served as Graduate Assistant and

Assistant Lecturer for two years.

Then in October 2011, he joined the School of Graduate Studies (SGS) of Haramaya

University to pursue his MSc. study in Animal Genetics and Breeding in the School of

Animal and Range Sciences.

vi

ACKNOWLEDGEMENTS

“I will praise thee forever, because thou hast done it” Ps. 52: 9.

I would like to thank the Almighty God with his mother Holy Saint Virgin Mary, the most

Gracious and the most Beneficent, who enabled me to reach this point and for kind-

hearted help in all aspects of my life.

I am grateful to my major supervisor, Dr. Halima Hassen from International Center for

Agricultural Research in the Dry Areas (ICARDA) for her kind supports, guidance and

advice during the course of this study. I am also thankful to my co- advisors: Dr. Kefelegn

Kebede from Haramaya University, Dr. Aynalem Haile and Dr. Barbara Ann

Rischkowsky from ICARDA for taking time out of their busy schedule to read my thesis

and provide me meticulous guidance and encouragement throughout the study period that

enabled this work to be concluded fruitfully. I owe special dept of appreciation to Dr.

Tadelle Dessie, ILRI, head of AnGR group for unreserved encouragement and my

colleagues Mr. Dereje Taddesse and Mr. Mekete Bekele (PhD candidates at Haramaya and

Addis Ababa Universities, respectively) for their comments and ideas throughout my

study period.

Mekasha Tafese, Asresu Yetayew, Ayele Abebe, Asfaw Bisrat and Grum Gebreyesus,

thanks all for your dedication and support during data collection; scientific, social and

friendly discussions and ideas that we shared. I am grateful to the staff of ICARDA-

Ethiopia Martha Sintayehu and Yodit Hailu for their encouragement and technical support.

I would like to thank ICARDA for providing me stipend and sponsoring this study. I am

also greatly indebted to Ethiopian Ministry of Education for financial assistance through

Haramaya University and Debre Berhan University for providing me study leave and

guarantee my salary during the study time. My heartfelt thanks and cordial appreciations

go to the Bati, Borena and Siti community; local agricultural extension agents in the

respective area; and Sirinka, Debre Berhan, Jigjiga and Yabello Pastoral and Dry land

Agriculture Research Center staffs for their cooperation during data collection period.

vii

ACRONYMS AND ABBERVATIONS

ADG Average Daily Gain

AFK Age at First Kidding

AFLP Amplified Fragment Length Polymorphism

AIC Akaike Information Criteria

AnGR Animal Genetic Resources

BC Body Condition

BIC Bayesian Information Criteria

BL Body Length

BL Body Length

BW Body Weight

CAHWs Community Animal Health Workers

CANDISC Canonical Discriminant Analysis

CCPP Contagious Caprine Pleuro Pneumonia

CG Chest Girth

CP Conceptual Predictive

CSA Central Statistics Agency

CTA Technical Center for Agricultural and Rural Co-operation

CV Coefficient of Variation

CW Chest Width

DISCRIM Discriminant analysis

DNA Deoxyribonucleic Acid

DPPA Disaster Preparedness and Prevention Agency

EL Ear Length

EL Ear Length

F1 First Filial Generation

FAO Food and Agricultural Organization

FAOSTAT Food and Agricultural Organization Statistical Database

FMD Foot and Mouth Disease

GLM General linear model

GTZ German Organization for Technical Cooperation

HL Horn Length

HW Height at Withers

viii

ACRONYMS AND ABBERVATIONS (Continued)

IBC Institute of Biodiversity Conservation

ICARDA International Center for Agricultural Research in the Dry Areas

IFAD International Fund for Agricultural Development

ILRI International Livestock Research Institute

KI Kidding Interval

LPAR Livelihood Profile of Amhara Region

LS Litter Size

masl meters above sea level

mtDNA mitochondrial Deoxyribonucleic Acid

NGOs None Governmental Organizations

PCR Polymerase Chain Reaction

PPI Pair of Permanent Incisor

PPR Pest des Petit Ruminants

PW Pelvic Width

PW Pelvic Width

R2 Coefficient of Determination

RAPD Random Amplified Polymorphic Deoxyribonucleic Acid

RFLP Restriction Fragment Length Polymorphism

RL Rump Length

SAS Statistical Analysis System

SC Scrotum Circumference

SCUK Save the Children United Kingdom

SES Short-Eared Somali

SNP Single Nucleotide Polymorphism

SSR Simple Sequence Repeats

STEPDISC Stepwise Discriminant Analysis

ix

TABLE OF CONTENTS

Title Page

STATEMENT OF AUTHOR iv

BIOGRAPHICAL SKETCH v

ACKNOWLEDGEMENTS vi

ACRONYMS AND ABBERVATIONS vii

TABLE OF CONTENTS ix

LIST OF TABLES xiii

LIST OF FIGURES xv

TABLES IN APPENDEX xvi

ABSTRACT xvii

1. INTRODUCTION 1

2. LITERATURE REVIEW 4

2.1. Origin and Domestication of Goats 4

2.2. Indigenous Goat Genetic Resources and Distribution in Africa 5

2.3. Ethiopian Indigenous Goat Genetic Resources and Distribution 6

2.4. Socio-Economic Importance of Goats 8

2.5. Methods of Animal Genetic Resources Characterization 8

2.5.1. Description/characterization of production systems 9

2.5.2. Phenotypic characterization 10

2.5.3. Molecular Genetic characterization 12

2.6. AnGR Conservation and Utilization Strategies 15

2.7. Reproductive Performance of Goats 15

2.7.1. Age at first kidding 16

x

TABLE OF CONTENTS (Continued)

2.7.2. Kidding interval and Litter Size 17

2.8. Production Performance of Goats 18

2.8.1. Birth weight 19

2.8.2. Pre-weaning growth rate and average daily gain 19

2.8.3. Weaning weight 21

2.8.4. Goat Milk 22

3. MATERIAL AND METHODS 23

3.1. Description of the Study Areas 23

3.2. Livestock Demography in the Study Areas 24

3.3. Sampling Strategy 26

3.4. Data Collection and Management 26

3.4.1. Description of production systems 26

3.4.2. Morphometric data collection 27

3.4.3. On-farm flock monitoring and evaluation 28

3.5. Data Analyses 29

4. RESULTS AND DISCUSSION 32

4.1. Description of Production Systems 32

4.1.1. General Household Characteristics 32

4.1.2. Farming and non-farming activities 34

4.1.3. Livestock composition and holding pattern 35

4.1.4. Flock structure 37

4.1.5. Purpose of goat keeping 38

4.1.6. Herding practices 40

4.1.7. Feed resources and feeding practice 43

4.1.7.1. Feed resources 43

4.1.7.2. Feed shortage and supplementary feeding 44

4.1.8. Water resources, watering frequencies and watering point 46

4.1.8.1. Common sources of water 46

4.1.8.2. Watering frequencies and distance 47

xi

TABLE OF CONTENTS (Continued)

4.1.9. Housing 48

4.1.10. Castration 50

4.1.11. Trait preferences 51

4.1.12. Breeding management 52

4.1.12.1. Breeding stock selection 52

4.1.12.2. Breeding buck ownership and mating system 53

4.1.12.3. Breeding buck management and duration in the flock 54

4.1.12.4. Breeding doe selection criteria 55

4.1.12.5. Breeding buck selection criteria 56

4.1.13. Reproductive performances 58

4.1.14. Goat milking 59

4.1.15. Producers perception on some adaptability traits of their goats 61

4.1.16. Marketing 62

4.1.17. Animal health management 63

4.1.18. Constraints associated with goat keeping 64

4.1.19. Major goat health problems 66

4.2. Phenotypic Description of Bati, Borena and Short-Eared Goat Populations 68

4.2.1. Qualitative characteristics 68

4.2.2. Quantitative characteristics 75

4.2.2.1. Quantitative variation for does 75

4.2.2.2. Quantitative variation for bucks 76

4.2.3. Relationships between body weight and other body measurements 78

4.2.4. Estimation of body weight of goats from other body measurements 81

4.2.5. Multivariate analysis 85

4.2.5.1. Stepwise discriminant analysis 85

4.2.5.2. Discriminant analysis 86

4.2.5.3. Canonical discriminant analysis 88

4.3. On-farm Goat growth Performance Evaluation and Monitoring 91

4.3.1. Growth performance 91

4.3.2. Average body weight at different ages (birth, 30, 90 and 180 days) 91

4.3.3. Average daily weight gain (birth - 90 days) 95

xii

TABLE OF CONTENTS (Continued)

4.3.4. Average daily weight gain (91-180 days) 96

5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 98

5.1. Summary 98

5.2. Conclusions and Recommendations 100

6. REFERENCES 102

7. APPENDICES 115

xiii

LIST OF TABLES

Table 1. Types and distribution of some African goats 6

Table 2. Distribution of documented indigenous goat types in Ethiopia 7

Table 3. Advantages and disadvantages of most popular molecular markers 14

Table 4. Age at 1st kidding of Ethiopian goats under traditional management conditions 17

Table 5. Kidding interval and litter size for Ethiopian goat types under traditional

management conditions 18

Table 6 . Birth weight, weaning weight and pre-weaning average daily gain of some

Ethiopian goat types under different management conditions 21

Table 7. Total number of livestock by type and zone 24

Table 8. Households’ gender, age category and level of education in the study areas 33

Table 9. Mean (±SE) and percentage of livestock species owned per household 36

Table 10. Purpose of goat keeping in the study areas 40

Table 11. Available feed resources during the dry and wet seasons of the year 44

Table 12. Common water sources in dry season 47

Table 13. Watering frequency and distance during dry season in the study areas (%) 48

Table 14. Ranking of goat trait preference of producers 52

Table 15. The proportion of producers who practiced breeding stock selection 53

Table 16. Type of natural mating systems 54

Table 17. Bucks’ average years of service recalled by owners 55

Table 18. Ranking producers selection criteria for breeding doe in the study areas 56

Table 19. Ranking producers’ selection criteria for breeding buck in the study areas 57

Table 20. Some reproductive performances as estimated by respondents 59

Table 21. Milk utilization, milking frequency and lactation length (days) 60

Table 22. Percentage of respondents in leveling goats’ adaptive trait by study area 61

Table 23. Types of veterinary services accesses in the study areas 64

Table 24. Goat production constraints as perceived by the respondents 65

Table 25. Ranking of major goat health problems as reported by goat producers 67

Table 26. Frequency (N) and percentage in brackets for each level of qualitative traits by

goat population 70

Table 27. Descriptive statistics of body weight (kg), body condition score and other body

measurements (cm) for does as affected by population types. 76

xiv

LIST OF TABLES (Continued)

Table 28. Descriptive statistics of body weight (kg), body condition score and other body

measurements (cm) for bucks as affected by population type. 78

Table 29. Pearson’s correlation coefficients of quantitative traits for bucks (above

diagonal) and does (below diagonal) 80

Table 30. Regression of live body weight on different body measurements for does 83

Table 31. Regression of live body weight on different body measurements for bucks 84

Table 32. Quantitative characters selected by stepwise discriminant analysis 86

Table 33. Number of observation and percent of classification in parenthesis for sample

population by sex using K-Nearest Neighbour method 88

Table 34. Squared Mahalanobis distances between sampled populations based on pooled

covariance 89

Table 35. Descriptive statistics (LSM±SE) of body weights (kg) from birth to 180 days of

age for Bati, Borena and Short-eared Somali goats 93

Table 36. Descriptive statistics (LSM±SE) of daily weight gain (birth-90 and 91-180 days)

for Bati, Borena and Short-eared Somali goats 97

xv

LIST OF FIGURES

Figure 1. Map of Ethiopia and selected provinces for the baseline survey and performance

monitoring studies 25

Figure 2. Goat flock structures in Bati, Borena and Siti areas 38

Figure 3. Locally made goat skin water container (qerbid) in Siti area 39

Figure 4. Mixed species stocking/herding systems: Bati (a), Siti (b) and Borena (c) 42

Figure 5. Feed shortages by months across study sites 45

Figure 6.Traditional adult goats shelter in Siti (a), Borena (b) and Bati (c) areas 49

Figure 7. Traditional kids house type in Siti (left) and Borena (right) 50

Figure 8. Association among qualitative traits categories via correspondence analysis 73

Figure 9. Physical appearances of indigenous Ethiopian adult goat populations 74

Figure 10. Spatial distributions of does (left) and bucks (right) on the first two canonical

variats (CAN1 and CAN2) 90

Figure 11. Male, female and overall growth rate trends of three young Ethiopian goats

(birth to 180 days) 94

xvi

TABLES IN APPENDEX

Appendix Table 1. Ranking farming and non-farming activities by study area 115

Appendix Table 2. Percentages of households castrate their buck and method of castration

used by study areas 116

Appendix Table 3. Ranking of category of goats sold first in study areas 116

Appendix Table 4. Best models for Bati does regression equation 117

Appendix Table 5. Best models for Bati bucks regression equation 117

Appendix Table 6. Best models for Borena does regression equation 118

Appendix Table 7. Best models for Borena bucks regression equation 118

Appendix Table 8. Best models for Short-eared Somali does regression equation 119

Appendix Table 9. Best models for Short-eared Somali bucks regression equation 119

Appendix Table 10. GLM analysis output of quantitative traits of female samples 120

Appendix Table 11. GLM analysis output of quantitative traits of male samples 121

Appendix Table 12. GLM analysis output of growth traits of Bati kids for the effect of sex,

parity and type of birth 122

Appendix Table 13. GLM analysis output of growth traits of Borena kids for the effect of

sex, parity and type of birth 123

Appendix Table 14. GLM analysis output of growth traits of Short-Eared Somali kids for

the effect of sex, parity and type of birth 124

xvii

ON-FARM PHENOTYPIC CHARACTERIZATION AND

PERFORMANCE EVALUATION OF BATI, BORENA AND SHORT

EARED SOMALI GOAT POPULATIONS OF ETHIOPIA

ABSTRACT

BY

Hulunim Gatew; BSc in Animal Production, Haramaya University, Ethiopia

Major Advisor: Halima Hassen; PhD in Animal breeding and Genetics, Free State University,

South Africa

Co-Advisors: Kefelegn Kebede; PhD in Animal breeding and Genetics, Martin Luther,

University, Germany

Aynalem Haile; PhD in Animal breeding and Genetics, Deemed University, India

Barbara Ann Rischkowsky; PhD in Agricultural Sciences, Justus Liebig,

University, Germany

The objectives of this study were to describe the production systems, the morphological

features, and growth and reproductive performances of Bati (Central Highland ecotype),

Borena (Long eared Somali ecotype) and Short-eared Somali indigenous goat populations

in their home tract, Ethiopia. The study covered Bati and Kalu districts for Bati goats in

Oromiya and South Wollo zones (Amhara Region), respectively; Yabello for Borena goats

in Borena zone (Oromia Region); and Shinille and Erer from Siti (the previous Shinille

zone, in Somali Region) for Short-Eared Somali goats. For production systems description

and morphological characterization of the three goat breeds a total of 601 heads of adult

goats comprising 162 Bati (128 females and 34 males), 246 Borena (201 females and 45

males) and 193 Short-eared Somali (139 females and 54 males) were selected. In addition,

flock monitoring were carried out and two PAs for each goat population were selected

and a total of 125 household flocks (46 Bati, 48 Borena and 31 Short-Eared Somali) were

monitored (beginning of April, 2013 to end December, 2013) to generate growth

performance data. In terms of number, goats were the predominant species in all surveyed

areas. The average (±SE) goat flock size (44.02±3.33) owned per household of Siti was

significantly (p<0.05) higher followed by Borena (23.08±1.94). Source of cash was a

primary objective of goat rearing in Borena and Bati areas, while milk production was

ranked 1st in Siti. A range of traits: body size, fast growth rate, milk yield, reproduction

rate, drought tolerance and disease resistance were some of the important performance

and adaptive traits preferred by the producers across study areas. Natural pasture (shrubs

and bushes) was found to be the major source of goat feed across the study areas. Age at

1st kidding in Bati, Borena and Siti areas averaged 14.98±0.24, 15.86±0.22 and

20.15±0.12 months and average kidding intervals of 7.95±0.19, 8.42±0.17 and

8.81±0.18monthswere also noted, respectively. The major challenges of goat husbandry

include feed and water shortage, disease incidence and recurrent drought with different

xviii

prioritization across areas. The common goat diseases reported in the study areas were

pneumonia, pasteurellosis, babesiosis, anthrax and goat pox, external parasites,

contagious caprine pleuro pneumonia (CCPP), coenurosis, diarrhea and pest des petit

ruminants (PPR). The studied goat populations have a wide range of coat colors including

plain brown (dark and light) (51.85%) which were the predominant coat color observed

on Bati goats of both sexes. Meanwhile, plain white coat color was most frequently

observed on Borena goats (71.54%) and only 36.27% in Short-eared Somali goat

populations. Though most quantitative traits showed slightly higher average values in the

Bati goats, differences with Borena goats were not significant (p>0.05),whereas Short-

eared Somali goats remained significantly (p<0.05) lower for most of the body

measurement characteristics. Average live weight of Bati, Borena and Short-eared Somali

does were 33.97±0.4, 31.49±0.36 and 24.67±0.28kg, respectively and the corresponding

values for bucks were 41.30±0.85, 40.04±1.21 and 30.62±0.67kg. Correlation coefficient

was consistently highest between live weight and chest girth in both sexes across the goat

populations. As a result, the stepwise multiple regression analysis revealed that chest girth

was the single variable of utmost importance in the prediction of live body weight except

for Short-eared Somali bucks, where body condition accounted the larger variation in

body weight. Though K-Nearest Neighbor Discriminant Function Analysis classified most

individuals of both sexes into their source population in all areas, the highest hit rate was

found in Borena does (96.02%) and in Short-eared Somali bucks (94.4%). The canonical

discriminant analysis depicted the largest Mahalanobis' distance between Borena and

Short-eared Somali goats while the least differentiation was observed between Bati and

Borena goats. Non-genetic factors (sex and parity of dam) and genetic factor (goat

ecotype) had significant (p<0.05) effect on the average live weight and daily weight gain

of young goats at different ages. However, type of birth had non-significant effect on daily

weight gain of all goat types and on live weight of Short-eared Somali kids at different

ages (birth, 30, 90 and 180 days). Bati kids had the heaviest overall live weight at birth

(2.70±0.05kg) followed by Borena (2.42±0.05 kg). Therefore, the growth performance of

these goat ecotypes is encouraging and can be further improved genetically through

selection.

Key words: Constraint ∙ Discriminant analysis ∙ live weight ∙ Management practices ∙

Morphological features ∙

1. INTRODUCTION

The World Development Report (2010) estimated that about 410 million people in Sub-

Saharan Africa live in absolute poverty, surviving on less than one dollar per day. The poor

have no access to the basic necessities of life such as food, clothing and decent shelter, are

unable to meet social and economic obligations, lack the skills for gainful employment, and

have few if any economic assets and a general lack of self-esteem. However, rearing of small

ruminants (sheep and goats) would have lasting effects in bringing about social change by

improving the incomes of these people (Okpecku et al., 2011).

Small ruminants provide their owners with a vast range of products and services. They

contribute to landless, rural farming, peri-urban and increasingly to urban households by

providing food, income, manure and clothing (Pollott and Wilson, 2009; Oluwatayo and

Oluwatayo, 2012; Kurnianto et al., 2013). According to these authors, they also make

important indirect contributions to households through the use of crop by-products,

integration with other farming enterprises, and in the social, cultural and religious aspects of

everyday life. In addition to these, there are no banking facilities in rural areas and an easy

way to store cash for future needs are through the purchase of small ruminants (IBC, 2004).

In Ethiopia, goats kept in different parts of the country for the purpose of food source, income

generation, socio-cultural wealth and source of other valuable non-food products used as raw

materials for various traditional household products manufactured in local cottage industries.

Goats in the lowlands of the country kept both for milk and meat production, whereas in the

highlands they are mainly kept for meat and income generation (Aschalew et al., 2000;

Tesfaye, 2009). Goat milk is used as food and medicine both in special preparations by

traditional healers as well in its raw state by ordinary people.

The wide ranging production systems of Ethiopia have further contributed to the existence of

a large diversity of farm animal genetic resources (IBC, 2004). According to the livestock

survey result (CSA, 2013), the country has an estimated 24.06 million heads of goats. This

puts the country eighth among the top ten countries (China, India, Pakistan, Bangladesh,

Nigeria, Sudan, Iran, Ethiopia, Mongolia and Indonesia) in the world and third in Africa (next

to Nigeria and Sudan) those possesses the largest number of goat populations (FAOSTAT,

2

2013). As a result, the indigenous goat types are widely distributed and are found in all

administrative regions of the country.

Despite the wide distribution and large size of the Ethiopian goat population, the productivity

per unit of animal and the contribution of this sector to the national economy is relatively low.

This may be due to different factors such as poor nutrition, prevalence of diseases, lack of

appropriate breeding strategies and poor understanding of the production system as a whole

(Tesfaye, 2009). Therefore, characterization of the production systems and the available

genetic resources is necessary to design improvement programs in the future.

Designing of improvement programs will only be successful when accompanied by a good

understanding of the different farming systems and when simultaneously addressing several

constraints e.g., feeding, health control, management, and cost and availability of credit and

marketing infrastructure (Baker and Gray, 2003). Understanding the existing small-scale goat

keepers’ diversity of management strategies (feeding, breeding, housing, watering, health

control) and the challenges they face enable to develop effective intervention strategies. The

characterization of local genetic resources (based on morphological traits) plays a very

fundamental role in classification of animals based on size and shape in turn which can be to

some extent reasonable economic indicator (Okpeku et al., 2011). Improved utilization of the

local genetic resources and prioritization for conservation will be added advantages.

Improvements were also too slow due to lack of identifying the actual on-farm situations and

weighting the socio-economic and cultural benefits of the animals for the poor farmers

(Workneh et al., 2003). To design improvement measures relevant to specific systems and

thereby properly respond to the growing domestic and foreign demands for live goats and

goat products; characterizing distinct goat breeds/populations, describing their external

production characteristics in a given environment and management, identifying the social and

economic constraints are important.

However, before the last decade, goat research was limited in certain areas and issues in

Ethiopia, due to lack of enough man power, limited budget allocation, limited funds from

3

donors. (Aschalew et al., 2000; Halima and Tessema personal communication). But these

days, the Ethiopian government gave more attention and the scenario has been changed. As a

result, different research works (particularly phenotypic and genetic characterizations research

activities) had been executed in different parts of the country by different organizations and

individuals (FARM Africa, 1996; Tesfaye, 2004; Tesfaye, 2009; Tesfaye, 2010; Grum, 2010;

Halima et al., 2012a; Halima et al., 2012b). Despite the researches done, information on

phenotypic characteristics, production systems and reproductive performances of different

indigenous goat populations is still scanty.

Although there are now considerable published researches on indigenous goat performance in

Ethiopia, much of the works published has the disadvantage of having been carried out only

under controlled conditions at research stations where the results may not reflect the

performance of goats’ in the communal (traditional) production systems in rural areas. In

addition, most of the performance results do not explained in relation with phenotypic

characteristics of the populations.

The majority of Ethiopian goat populations (70%) are kept by pastoralists and agro-

pastoralists in arid and semi-arid lowlands (Alemayehu, 1993). South Wollo (eastern part) and

Oromiya Administrative Zones of Amhara Region, Siti zone of Somali Region and Borena

Zone of Oromia Region are lowland parts of the country, where Bati, Short-eared Somali and

Borena goat populations found respectively. Characterizing these goat populations and

describing their production environment will be very essential to design management and

utilization strategies. Therefore, this study was designed with the following objectives:

To carry out systematic survey and generate information on indigenous goat populations

utilization, management practices and challenges

To describe and characterize the physical characteristics of indigenous goat populations

To characterize the growth and reproductive performances of the selected indigenous goat

populations in their production system and environment

4

2. LITERATURE REVIEW

2.1. Origin and Domestication of Goats

The domestic goat (Capra hircus) is an important livestock species throughout the entire

Asian and African continents (Missohou et al., 2006). They are the earliest domestic animal

and probably the first ruminant livestock, after the wolf was domesticated (Zeder and Hasse,

2000). There are two reasons for this: firstly, the wild goat was reported to be present in the

regions of southwest Asia during the time when agriculture was developing. Secondly, the

goat is an extremely hardy animal, hence, could have withstood the rigors of being reduced to

the state of domestication better than other ruminants.

Despite their importance, the origins of goats remain uncertain, controversial and poorly

understood (Luikart et al., 2001). However, archaeological evidence indicates that goats were

one of the first animals to be domesticated by man around 10,000 years ago, in the Ganj-

Darch in the Zagros mountain pastures (Iran) (Zeder and Hasse, 2000). Luikart et al. (2001)

sequenced the first hyper-variable segment of the mtDNA control region of 406 goats

representing 88 breeds originating from 44 countries throughout Europe, Asia, Africa, and the

Middle East. Phylogeographic analysis revealed that three highly divergent goat lineages

(estimated divergence >200,000 years ago), with one lineage occurring only in eastern and

southern Asia. These results, combined with archaeological findings, suggest that goats and

other farm animals have multiple maternal origins with a possible center of origin in Asia in

the region known as Fertile Crescent (Jordan, Syria, Turkey, Iraq and Iran including Tigris

and Euphrates rivers as well as Zagros Mountain) (Zeder and Hasse, 2000). In their study,

from the pattern of goat mtDNA diversity suggested that all three lineages have undergone

population expansions, but the expansion was relatively recent for two of the lineages

(including the Asian lineage). Whereas some studies have suggested that an independent

domestication in Pakistan gave rise to the Cashmere breeds (Porter, 1996).

The wild ancestors of domestic goats were believed to include the Ibex (Capra ibex) and the

Bezoar (Capra aegagrus), animals of steep hills and mountain sides in Asia Minor. Later,

5

domesticated goats spread to North Africa and Southern Europe. The lands they inhabited

were either hot and dry, or cold and barren with few plants (Machugh and Bradley, 2001).

The wild endemic species of walia ibex (Capra ibex walie) has been maintained in a wildlife

reserve area in Ethiopia Simien mountains national park, (SMNP). Due to closer genetic

similarity between Walia ibex (Capra ibex walie) and domestic goat (Capra hircus) and the

location of the park around the vicinity of human settlements, there was a fear of

interbreeding between domestic goat (Capra hircus) and Walia ibex (Capra ibex walie)

(Alemayehu et al. 2011). However, these authors concluded that there is no genetic

introgression between Walia ibex (Capra ibex walie) and domestic goats (Capra hircus).

2.2. Indigenous Goat Genetic Resources and Distribution in Africa

Indigenous goats of Africa have been described as large, small and dwarf type (Table 1).

Large types, which may also have disproportionately long legs, are found along the southern

fringe of the Sahara and in Southern Africa. The small type is mainly distributed in Eastern

Africa whereas the dwarf types, which are also to some extent tolerance of trypanosomiasis

and more prolific, are found mainly in humid Western Africa (FAO, 1985).

From the world goat population (861.9 million), the largest number is found in Asia, followed

by Africa, representing about 59.7% and 33.8%, respectively (FAOSTAT, 2008). In Africa,

these animals are spanned in Nigeria, Ethiopia, Sudan and Somalia. From a total of 351 goat

breeds of the world, about 146 goat breeds are found in Asia and 59 in Africa (Devendra,

1998).

6

Table 1. Types and distribution of some African goats

Goat types/breeds Distribution Reference

Large goats (Africander, Pafuri, Tswana,

Swazi, Ndebele, Landim, Shukria, Sudan

Desert, West African Long-Legged)

Southern fringe of

Sahara and in

Southern Africa

FAO, 1985

Small goats (Red Sokoto, Afar, Mubende,

Kigezi, Boran,Masai, Rwanda and Burind,

Malawi, Zimbabwe (Mashona))

Eastern Africa

Dwarf goats(West African dwarf) Western Africa

2.3. Ethiopian Indigenous Goat Genetic Resources and Distribution

Ethiopia has diverse topographic, climatic conditions and wide production systems (IBC,

2004). The country has long been recognized as source of large diversity of farm animal

genetic resources (e.g., goat, sheep, and cattle) in which an estimated 24.06 million heads of

goats are reared (CSA, 2013). Based on the goat physical, morphological and functional

characteristics descriptors, the Ethiopian goats have been phenotypically classified into 12

types (Table 2). Tesfaye (2004) has classified these indigenous goat types of Ethiopia in to 8

distinct genetic entities using genetic DNA markers, These are:- Arsi-Bale, Gumez, Keffa,

Woyto-Guji, Abergalle, Afar, Highland goats (previously separated as Central and North

West Highland) and the goats from the previously known Hararghe, South eastern Bale and

Southern Sidamo provinces (Hararghe Highland, Short-eared Somali and Long-eared Somali

goats). Based on their morphological characteristics, Halima et al. (2012a) characterized six

goat ecotypes (Gumuz, Begia-Medir, Agew (West Amhara Region goat population) and Bati,

Central Abergelle and Abergelle (east Amhara Region goat population) found in Amhara

Region of Ethiopia and clustered in to two main groups. Gumuz, Agew and Begie-Medir the

first group and Bati, Abergelle and Central Abergelle as the second group. These goat

populations also genetically characterized using 15 microsatellite markers and revealed

reseanable amount of genetic diversity within and between populations (Halima et al., 2012b).

7

Table 2. Distribution of documented indigenous goat types in Ethiopia

Goat types Synonym Distribution

Barka Bellenay,

Beni Amer

Northern and northwestern Ethiopia near the

border with Eritrea and the Sudan

Long

eared

Somali

Digodi, Melebo,

Boran Somali,

Benadir, Gigwain

Rangel and of thesouthern Ogaden, Bale,Borana

and Southern Sidamo With the Somali and

Borana Pastoralists

Short

eared

Somali

Ogaden, Mudugh,

Dighier,Abgal, Issa-

Somali, Bimal

Northern and Eastern Ogaden and around Dire

Dawa

Western

Highland

Agew Highlands of Western Ethiopia (Gonder,Gojjam,

Wollega and Shoa)

Western

Low land

Gumuz Lowlands of Western Ethiopia (Metekel,

Assosa, and Gambella)

Woyto-

Guji

Woyto, Guji, Konso North Omo, South Omo, Sidamo, Borana

Abergelle Na Southern Tigray, North Wollo, and South

Gonder

Afar Adal, Assaorta,

Denakil

Afar region and parts of Eritrea and Djibouti

with the Afar Pastoralists

Central

Highland

Brown Goat, Kaye Highland of Central Ethiopia from Tigray

through Wollo, Gonder to Shoa

Hararghe

Highland

Kotu-Oromo Highlands of Eastern and Western Hararghe

Keffa

Arsi-Bale

NA

Gishe, Sidama

Keffa and adjoining parts of Kembata and

Hadiya

Arsi and Bale, higher altitudes of Sidamo and

West Shewa

Source: FARM-Africa; NA= Not Available

8

In lowland areas, goats rely on browsing and grazing whereas in the highlands they depend on

communal grazing, fallow lands and crop residues (Aschalew et al., 2000). Therefore, based

on the availability of land, feed and reliability of crop production, flock sizes of goat vary

with the production system and the production environment. Due to availability of grazing

area in lowlands and crop residues in moist highlands, larger flocks are found in lowlands and

moist highlands than highly populated and sub-moist highlands areas (Solomon et al., 2010).

2.4. Socio-Economic Importance of Goats

Small ruminants have economic importance to small-holder farmers including female-headed

households. The total income share from small ruminants tends to be inversely related to size

of land-holding, suggesting that small ruminants are of particular importance for landless

people especially for rural women (Oluwatayo and Oluwatayo, 2012). In some cultural

settings, women are often not entitled to own land. For instance, African rural women (such

as in Nigeria, Kenya, and Tanzania) have limited access to household’s land and receive

limited land use rights from their husbands (Quisumbing et al., 2001). As a result, crop

production provides seasonal employment; hence, rearing of small ruminants would provide

an employment opportunity and income throughout the year.

In Ethiopia, livestock in general goats in particular plays a very important role in the lives of

households. They have a great role in the economy of farming community of the country.

Sale of goats and goat products (meat, skin and milk) by farming communities is the major

source of cash for purchase of clothes, grains and other essential household commodities

(Deribe, 2009; Tesfaye, 2009). In addition, goats are raised mostly to safeguard against crop

failure and unfavorable crop prices in intensive cropping areas. In Ethiopia, the purpose of

keeping goats by smallholder farmers is to generate income, for labor, wage payment

followed by food crop purchase, input purchase, school fee and as means of tax in that order

(Deribe, 2009; Tesfaye, 2009).

2.5. Methods of Animal Genetic Resources Characterization

Characterization, inventory and monitoring of the trends of AnGR diversity were among the

strategic priority areas of Global Plan of Action for Animal Genetic Resources (FAO, 2007).

9

Most breeds originating from industrialized countries are well-defined and phenotypically

distinct and were genetically isolated throughout the course of their development. In contrast,

Asian and African livestock breeds most often correspond to local populations that differ only

gradually according to geographical separation. In addition, breeds with different names may

sometimes have a recent common origin, while in other cases their uniqueness has been

eroded by cross-breeding (FAO, 2011).

Characterization is defined as the description of a character or trait of an individual. The word

‘characterize’ is also a synonym of ‘distinguish’, that is, to mark as separate or different, or to

separate into kinds, classes or categories. Thus, characterization of genetic resources refers to

the process by which populations or ecotypes are identified or differentiated. Characterization

of AnGR encompasses all activities associated with the identification, quantitative and

qualitative description, and documentation of breed populations and the natural habitats and

production systems to which they are or are not adapted. The aim is to obtain better

knowledge of AnGR, of their present and potential future uses for food and agriculture in

defined environments, and their current state as distinct breed populations (FAO, 2007). The

weight given to each depends on the country (e.g. whether it is developed or developing) and

the objective (e.g. improvement, conservation or breed differentiation) (FAO, 2012).

2.5.1. Description/characterization of production systems

Production environments, intensities and purposes of production, vary greatly within and

across countries. The majority of small ruminant populations (70%) found in the developing

countries are in grazing system. The grazing systems are primarily found in the more marginal

areas which are unfit for cropping because of topography, low temperature or low rainfall

(Steinfeld et al., 2006).

In Ethiopia, depending on the environmental and social conditions different management

systems are prevailing in goat production. The majority of systems are described under low

input production system which characterized by land scarcity, severe resources degradation

and recurrent drought. It accommodates more than 95% of the livestock population (IBC,

2004). Based on the prevalent agricultural activity, Getahun (2008) reported four production

10

system categories. This includes, annual crop-based systems (Northern, North-Western and

central Ethiopia), perennial crop-based systems (mainly Southern and South-Western

highlands), cattle-based systems (agro-pastoral and arid areas), and small ruminant dominated

systems (pastoral, Eastern and North-Eastern areas). Considering degree of integration with

crop production and contribution to livelihood, level of input and intensity of production,

agro-ecology, length of growing period and relation to land and type of commodity to be

produced, Solomon et al. (2008) also put the prevailing production systems in to three major

categories. These are: highland sheep–barley system, mixed crop–livestock system, and

pastoral and agro-pastoral production systems. Understanding and description of the

production systems is useful in the design of development strategies, in particular for

identifying target populations and priorities and opportunities for development (Fernandez-

Rivera et al., 2004).

According to Steinfeld et al., (2006), due to rapidly evolving socio-economic conditions;

many of the systems that are the result of a long evolution are under pressure to adjust to large

intensive livestock production units. In Ethiopia, Solomon et al., (2008) also stated that

ranching, urban and peri-urban (landless) sheep and goat production systems are the other

production systems that are not practiced widely in the country but have a future.

2.5.2. Phenotypic characterization

Phenotypic characterization of AnGR is the process of identifying distinct breeds or

populations by describing their external and production characteristics in a given environment

and under given management, taking into account the social and economic factors. The

information generated by characterization studies is essential for planning the management of

AnGR at local, national, regional and global levels (FAO, 2012). The Global Plan of Action

for Animal Genetic Resources (FAO, 2007) recognizes that “a good understanding of breed

characteristics is necessary to guide decision-making in livestock development and breeding

programs”.

Nowadays, there is a great interest worldwide in conservation and improved utilization of

goat genetic resources. Phenotypic characterization is essential in mapping out an inventory of

11

characteristics peculiar to a group of animals and sustainable use of its animal genetic

resources. Lack of information on characterization of genetic resource may lead to

underutilization of that resource, its replacement and dilution through cross breeding despite

their local adaptation to prevailing environmental constraints (Manzi et al., 2011).

According to FAO (2012), phenotypic characterization activities are technically and

logistically challenging. Ensuring that they are well targeted (collect data that are important to

the country’s priority AnGR and livestock-development activities) and are carried out in an

efficient and cost effective manner requires thorough planning and careful implementation.

Valid comparisons among livestock breeds or populations, whether nationally or

internationally, require the development and use of standard practices and formats for

describing their characteristics. Such standards and protocols are also needed for assessing

requests for the recognition of new breeds.

Breed characterization through phenotype, is based on the description of qualitative and

quantitative traits. Qualitative traits to be recorded during phenotypic characterization of goat

breeds are sex, estimated age (dentition), coat color pattern and type, horn shape, horn and ear

orientation, facial (head) and back profile as well as presence or absence of wattles, beard,

and ruff. Whereas quantitative traits include the measurements of body length , height at

withers, chest girth, chest depth, shoulder point width, head length, head width, rump length,

pelvic width, horn length , ear length, shin circumference and scrotum circumference for

males (FAO,2012).

In addition to physical characteristics, phenotypic characterization of livestock breeds also

includes information on population size, flock size and composition, production estimates and

information on the production environment and husbandry conditions, which are known to

play vital roles in trait expression. This method provides basic evidence for the variation

between and within livestock populations, which could be utilized for selection purposes

(Okpeku et al., 2011).

12

2.5.3. Molecular Genetic characterization

Phenotypic characterization provides a crude estimate of the average of the functional variants

of genes carried by a given individual or population. Now a day, genomic and bioinformatics

advances have created opportunities to characterize livestock in terms of the function of their

genes. Molecular genetic characterization, by itself or in conjunction with other data

(phenotypic traits or geo-referenced data), provides reliable information to assess the amount

of genetic diversity. Information about the genetic make-up of populations also helps decision

making for conservation activities (Boettcher et al., 2010).

Protein polymorphisms were the first molecular markers used in livestock. A large number of

studies, particularly during the 1970’s, have documented the characterization of blood group

and allozyme systems of livestock (Baker and Manwell, 1980). However, the level of

polymorphism observed in proteins is often low which has reduced the general applicability

of protein typing in diversity studies. With the development of Polymerase Chain Reaction

(PCR) and sequencing technologies associated with automatic and/or semi-automatic large

scale screening system, several molecular markers have been widely used for genetic diversity

and phylogenetic analyses (Charoensook et al., 2013) in livestock breeds or populations. A

number of molecular markers are available to detect polymorphisms at the DNA level. The

most popular markers in genetic diversity studies are simple sequence repeats (SSR) or

microsatellites, restriction fragment length polymorphism (RFLP), random amplified

polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), single

nucleotide polymorphism (SNP) and mitochondrial DNA (mtDNA) analysis (Charoensook et

al., 2013). They can be used to build up genetic maps and to evaluate differences between

markers in the expression of particular traits that might indicate a direct effect of these

differences in terms of genetic determination on the trait (Vignal et al., 2002). The advantages

and limitations of most popular molecular markers are summarized in Table 3.

Even though, the commercial applicability of genetic markers has been relatively limited due

to limitations of the technologies available (Dekkers, 2004), the entire genomic sequences of

several livestock species are now offered. The increased quantity of genomic information

considerably facilitates candidate gene analysis and makes genomic scans more accurate.

13

Consequently, Candidate genes can be chosen based on both their biological function and

their genomic position (Schulman et al., 2009). Since the costs for DNA sequencing have

decreased (Shendure and Ji, 2008), in the coming years, even more effective sequencing

systems will be available and allow very low cost whole genome sequencing. However, due

to the faster increasing of tools for molecular characterization of livestock breeds, storing,

organizing, analyzing, and exploitation will be the future challenge for researchers.

The Food and Agricultural Organization (FAO) of the United Nations has proposed a global

program for the management of genetic resources using molecular methodology for breed

characterization (Bjornstad and Roed, 2001). However, in Ethiopia, only limited goat genetic

characterization activities (Tesfaye, 2004; Halima, 2012b) had been conducted on some goat

breeds using microsatellite markers.

14

Table 3. Advantages and disadvantages of most popular molecular markers

RFLP = restriction fragment length polymorphism, RAPD = random amplified polymorphic deoxyribonucleic acid, AFLP = amplified fragment length

polymorphism, SSR = simple sequence repeats, SNP = single nucleotide polymorphism, mtDNA = mitochondrial Deoxyribonucleic Acid

Marker Advantages Disadvantages References

RFLP Produces co-dominant, stable and reproducible and

selective neutrality

Long methodology, labour intensive and require

high quality and large quantities of DNA

Mburu and Hanotte, 2005

RAPD Cost effective, simple and quick, large number of

bands are produced and no prior sequence

knowledge is necessary

Detection of polymorphism is limited,

reproducibility of results maybe be inconsistent

and dominant markers

Mburu and Hanotte, 2005;

Charoensook et al., 2013

AFLP Sensitive, large number of polymorphisms is

generated and no prior sequence information or

probe generation is needed

Expensive, dominant markers and technically

demanding

Mburu and Hanotte, 2005

SSR Low quantities of template DNA required, high

genomic abundance, random distribution, high

level of polymorphism, different microsatellite can

be multiplied, co-dominant markers, high

reproducibility, wide range of applicability,

amenable to automation etc.

Expensive, homoplasy due to different forward

and backward mutations may underestimate

genetic divergence, underlying mutation model

largely unknown time consuming, etc.

Mburu and Hanotte, 2005

SNP Highly reproducible and very informative Expensive and previous know ledge of sequence

required

Mburu and Hanotte, 2005;

Charoensook et al., 2013

mtDNA Applicable to all biological source material, very

high sensitivity and maternal inheritance

Expensive, heteroplasmy (few single base pair

difference might be there in different cells of the

same individual unlike the nuclear DNA

Kisa, 2006; Mburu and

Hanotte, 2005

15

2.6. AnGR Conservation and Utilization Strategies

Animal genetic resource conservation involves all human activities including strategies, plans,

and actions undertaken to ensure that the diversity of farm animal genetic resource is being

maintained to contribute to the food and agriculture production and productivity, now and in

the future (Kohler-Rollefson, 2004). Conservation strategies can be categorized as either in-

situ conservation where the breed is maintained in the environment in which it is developing,

or ex-situ conservation for all other cases. The latter can be further divided into ex-situ in vivo

conservation where breeds are kept in a different environment including farm parks, and as

ex-situ in vitro, utilizing cryogenic storage of semen, oocytes, embryos or DNA (FAO, 1999).

Conserving breeds is comparable to the conservation and maintenance of cultural-historical

aspects, buildings and environments (Maijala et al, 1984). Results from cross bred goats in an

upgrading program in Ethiopia showed no increased benefits compared to indigenous goats

under improved management (FAO, 2002). It seems that the emphasis is on the improvement

of local breeds rather than on the conservation of the breeds. Failure to conserve domesticated

genetic resources will definitely lead to a situation where a large portion of goat’s genome

will be on the verge of being lost. Understanding the diversity, distribution, basic

characteristics, comparative performance and the current status of animal genetic resources is

essential for efficient, and sustainable use, development and conservation, which enables

farmers to determine which breed to use under prevailing production conditions (FAO, 2007).

Therefore, effective conservation and use of animal genetic resources is vital for creating and

maintaining sustainable increases in the productivity of healthy food for mankind, as well as

contributing to the increased resilience of biodiversity. Nevertheless, the rates of AnGR losses

in developing countries have notably increasing at higher rates (Anderson, 2003).

2.7. Reproductive Performance of Goats

Reproduction efficiency is one of the most important economic traits in terms of livestock

production. Maintaining good reproductive functions in the herd is pivotal to the success of

any livestock production system and has to be given priority (Barding et al., 2000).

Productivity and profitability of a goat flock are measured by age of goats at first kidding,

16

kidding interval, type of birth or litter size and mass of kids at birth, weaning (Song et al.,

2006) and rate of morbidity and mortality. The evaluation of the reproductive performance of

a local breed of goats can provide important information to understand its’ productive

potential using local resources. Such information is very important to undertake any breed

improvement work in the rural areas.

Performance testing is the comparative evaluation of animals for production and reproduction

traits of economic importance that plays pivotal role in sustainable animal production

industry. The level of reproductive performance is dependent on the interaction of genetic and

environmental factors (Greyling, 2000) and has to be given priority (Barding et al., 2000).

Song et al. (2006) stated that reproductive efficiency of goats is determined by age of goats at

first kidding, kidding interval, birth type (litter size), mass of kids at birth and weaning.

2.7.1. Age at first kidding

Age at first kidding can be defined as the age at which does give birth for the first time. It is a

function of puberty, age at first breeding and conception and successful completeness of

pregnancy. These reproductive characteristics including age at first kidding (AFK) are

influenced by many factors such as genetic makeup of an individual, physical environment,

nutrition and time of birth (Alexander et al., 1999). The age at which animals first begin to

breed is important for two reasons: early breeding can improve the rate of turnover of

generations of animals and so speed up genetic progress as well as lifetime reproductive

efficiency is greatly increased by early breeding. Age at first kidding can be expressed either

percentage of mature body weight or in months (Table 4).

Warui et al. (2007) reported age at first kidding for Gabra and Rendille Kenya goats ranged

from 12 to 36 months. According to the same authors, age differences at first birth for Gabra

and Rendille goats in Kenya were significant in the dry years (p<0.001) and in the wet years

(p<0.05). During the dry years, many of the does had their first birth at an age older than 18

months, whereas in wet years at younger age than 18 months.

17

Table 4. Age at 1st kidding of Ethiopian goats under traditional management conditions

2.7.2. Kidding interval and Litter Size

Kidding interval (KI) refers to the number of days between successive parturitions. Whereas

litter size (LS) or number of kids in the litter as defined by Alexandre et al. (1999) is a total

number of born kids per kidding per goat. Kidding frequency and litter size are important

components of an efficient kid production system. The former is an important predictor of life

time productivity (Awemu et al., 1999) whereas the latter is an important trait for selection of

goats to produce next generation and increase of meat and milk production and it seemed to

be the most useful selection criterion for genetic improvement of meat production.

Amoah and Gelaye (1990) stated that litter size was under significant influence of goat age

and parity, whereas Awemu et al. (1999) reported parity, year and season as factors of

importance for goat litter size. According to Greyling (2000), there was no significant

difference in the post-partum anoestrus interval for does giving birth to different numbers of

offspring. Amoah et al. (1996) have showed litter size, breed and parity can affect gestation

period.

The prolonged kidding interval was responsible for a decrease in productivity of goats

(Awemu et al., 1999). At least three times kidding is expected per two years under normal

circumstances (Girma, 2008). It was suggested kidding interval should not exceed 8 months

Goat type Age at 1st kidding

(months)

References

Arsi-Bale (Alaba) 12.1 Tsedeke, 2007

Afar 24 Wilson, 1991

Arsi-Bale 13 Samuel, 2005

Arsi-Bale ( Loka Abaya) 14.8±0.3 Endeshew, 2007

Keffa 12.5 Belete, 2009

Somali/Boran 30 Wilson, 1991

Unspecified ( Metema) 13.6±2.44 Tesfaye, 2009

18

(245 days); however, the average kidding interval for the long legged West African goat in

pastoral system was reported as 328 days (Wilson, 1991).

Akpa et al. (2011) reported litter size ranged from 1 to 4 with the mean of 1.7 in Nigeria goats

under traditional management condition. Litter size in this study showed a tendency to

increase from 1st to 5th parity and a reduction in the 6th. These results indicates that the parity

level in which doe’s prolific ability reaches its peak is between the 4th and 5th parity, thus

culling of does from the herd can starts beyond the 5th parity. It may be economically unwise

to cull a doe at the early parities (except for ill-health) when the full genetic potential of their

reproductive rate has not yet been fully expressed. Multiple births were common in this study

in wich 44% (single), 40.5% (twins) and 14.7% (triplets) (Akpa et al., 2000). However,

comparable results were also reported by Amoah et al. (1996) that the most frequent litter size

was twin (48.1%) followed by single (34.6%) births. Litter size varies between 1.08 and 1.75

with an average of 1.38 for tropical breeds (Girma, 2008). Kidding interval and LS for some

Ethiopian goat types under traditional management conditions is presented in Table 5.

Table 5. Kidding interval and litter size for Ethiopian goat types under traditional

management conditions

Goat types KI (months) LS References

Arsi-Bale (Alaba) 6.9 1.75 Tsedeke, 2007

Arsi-Bale 8.07 NA Samuel, 2005

Arsi-Bale (Boka Abaya) 6±0.2 2.07 Endeshew, 2007

Keffa 7.9 1.7 Belete, 2009

Unspecified (Metema) 8.4±1.37 NA Tesfaye, 2009

Unspecified (Alaba) 9.05±0.08 1.47±0.04 Deribe, 2009

NA-Not available

2.8. Production Performance of Goats

Growth in animals is defined as a differentiation and increase in body cells (Bathaei and

Leroy, 1996). Growth rate, body size and changes in body composition are of economic

importance for efficient production of meat animals. According to Bathaei and Leroy (1996),

19

animal growth can be expressed as the positive change in body weight per unit of time or by

plotting body weight against age. The increase in body weight of farm animals is mainly a

reflection of the growth of carcass tissues consisting of lean meat, bone and fat. Growth rate

of lambs or kids, particularly during the early ages of growth, is strongly influenced by breed

type, milk production potential of the female animals, the environment under which the

animals are maintained, including the availability of adequate feed sources both in quantity

and quality (Bathaei and Leroy, 1996; Kassahun, 2000). Growth rate can be observed into

pre-weaning average daily gain and post-weaning daily gain (Luginbuhl, 2002).

2.8.1. Birth weight

Birth weight is the starting point to determine pre-weaning growth rate. It can be affected by

season of the year, breed type, sex and litter size (Browning, 2007). Madibela et al. (2002)

reported about Tswana goats’ birth weight as was positively correlated with the growth rate of

the animals. Negative association between birth weight and litter size had also been reported

(Song et al. 2001; Deribe, 2009; Banerjee and Jana, 2010). Song et al. (2001) reported the

mean birth weight of the Korean native goat kid of 2.04 kg, which varies from single

(2.28kg), twin (2.11kg) and triplet (1.64kg) birth types. Other similar studies were also

reported about birth weight as significantly affected by breed and sex types (Lusweti, 2000;

Zhou et al., 2003). Bushara et al. (2013) reported the birth weights of kids in Sudan (Southern

Kordofan State) goats were 2.10, 2.02 and 1.79 kg for single, twin and triplets, respectively.

Birth weights of some Ethiopian goats under different management conditions are also

presented in Table 6.

2.8.2. Pre-weaning growth rate and average daily gain

The pre-weaning average daily gain period reflects the genetic potential of the growing

animal and an important production trait to be considered (Luginbuhl, 2002). Rapid growth is

a crucial criterion for the improvement of meat production in goats (McGowan and Nurce,

2000) and other livestock species. Growth during the pre-weaning period is largely influenced

by the maternal milk production potential and competition for it amongst litter mates. In

addition, it can be also influenced by the energy level offered to the doe during lactation

(Sibanda et al., 1999).

20

Research results (Zahraddeen et al., 2008; Belay and Mengistie, 2013) on goats in Nigeria and

Ethiopia, respectively indicated that single born kids exhibited a higher growth rate than twins

from birth to weaning. Different authors (Das and Sendalo, 1990; Akpa et al., 2011) reported

male goats were significantly heavier and grew faster than female goats. According to

Andries (2013) working on Kentukey meat goats, sex of goat kids had a significant effect on

weaning weight and pre-weaning average daily gain. Inyangala et al. (1990) reported that

parity was a significant source of variation for growth rate.

For meat production goats, heavier body weights and faster growth rates are the most

important traits (Lu, 2001; Bushara et al., 2013). Boer goats are known to have a higher

growth rate compared to other goat breeds (Malan, 2000). Boer goats can grow in the first 12

months 200 g/day or more under good management conditions. Average growth rates for

male Boer goats were recorded as 291, 272, 245 and 250 g/day from birth to 100, 150, 210

and 270 days, respectively and corresponding rates were 272, 240, 204, and 186 g/day in

females (Campbell, 2003; Cited by King, 2009). In Ethiopia, this breed has been used in

crossing with the indigenous goat breeds to improve their productivity. The Abergelle goat

breed is one of the breeds that are used for crossing with Boer goats. Average live weight

change recorded at three month, six month and one year for first filial generation (F1) of male

Boer-Abergelle crossbreds were 104, 96.3 and 73.8 g/day while 102, 91.1 and 64.6 g/day

were in females (Belay et al., 2014). Weaning weight and pre-weaning average daily gain of

some Ethiopian goat types under different management condition is presented in Table 6.

21

Table 6 . Birth weight, weaning weight and pre-weaning average daily gain of some Ethiopian

goat types under different management conditions

Goat type Management

Type

Birth

weight

(Kg)

Weaning

weight(k

g)

Pre-weaning

average daily

gain(g/day)

References

Abergelle Intensive 2.4-2.6 6.0-8.9 33-55 Birhane and Eirk,

2006

Arsi-Bale Intensive 2.45 9.2 71.76 Mehlet, 2008

Arsi-Bale Traditional 2.28 8.39 72.21 Tatek et.al., 2004

Arsi-Bale (Loka Abaya)

Traditional 2.52 9.56 NA Endashew, 2007

Keffa Traditional 2.78 9.0 NA Belete, 2009

Somali Station 3.19 11.67 61.25 Zeleke, 2007

Toggenberg X

Arsi-Bale

Station 2.57 9.43 NA Girma, 2002

NA-Not available

2.8.3. Weaning weight

In some production systems, kids are sold at weaning (Luginbuhl, 2002); hence, weaning

weight is crucial and has great economic importance in meat goat production. Deribe (2009)

carried out an on-farm performance evaluation study on indigenous sheep and goats in Alaba,

Southern Ethiopia and reported that because of dependency of weaning on growth rate of

kids, there is no definite time of weaning. Growth rate is determinant for weaning than age;

hence, dams with good mothering ability are dried earlier than from those with poor

mothering ability. Weaning weight indicate the mothering ability of the herd as well as the

growth potential of the kids (Coffey, 2002). According to Boggs and Merkel (1993) weaning

weight can be used to estimate growth rate, and it is an excellent indicator of productivity

because it reflects litter size, mothering ability and milking ability too.

Weaning weight of Kacang and Peranakan Etawah goat was significantly affected by parity,

type of birth and litter weight at birth (Sodiq, 2004). According to the result of this author,

averages of weaning weight of both breeds tend to increase with the advance in parity up to

22

the 4th

parity and slightly decrease thereafter. Averages of litter weight at weaning of both

breeds increased progressively with the advance in type of birth. The regression of birth

weight on weaning weight was highly significant, and with each 1 gram (gm) increase in birth

weight there is an increase of 4.48 gm and 3.37 gm weaning weight of Kacang and Peranakan

Etawah goats, respectively. The weaning weights of some Ethiopian goat types under

different management system are presented in Table 6 above.

2.8.4. Goat Milk

Goat milk has played a very important role in health and nutrition of young and elderly. It has

also been known for its beneficial and therapeutic effects on the people who have cow milk

allergy. These nutritional, health and therapeutic benefits enlighten the potentials and values

of goat milk and its specialty products (Yangilar, 2013). It is more advantageous over cow or

human milk having better digestibility, alkalinity, buffering capacity, and certain therapeutic

values in medicine and human nutrition, as a result the need of goat milk as infant diet is

growing rapidly worldwide (Bosworth and Slyke, 2009) and it commands higher price than

cow milk. According to these authors goat milk is very close in composition to breast milk.

23

3. MATERIAL AND METHODS

3.1. Description of the Study Areas

The study covered five districts in four administrative zones: representing Bati and Kalu for

Bati goats in Oromiya and South Wollo zones (Amhara Region) respectively; Yabello for

Borena goats in Borena zone (Oromia Reggion); Erer and Shinille from Siti (the previous

Shinille zone) for Short-Eared Somali goats (Somali Region) (Figure 1).

Site 1: Oromiya and eastern part of South-Wollo

Oromiya and South-Wollo zones are two of 11 administrative zones of Amhara Regional

State. Kemisie and Dessie are the capital towns of Oromiya and South Wollo zones which are

located 325km and 400km away north of Addis Ababa, respectively (Negussu, 2006). South

Wollo has a varied topography, from the dry plains at 1000 masl altitude in the east to the

high peaks above 3500masl altitude in the west whereas the elevation of Oromiya

administrative zone ranges 1000-2500masl. The economy is based on crop production but

livestock rearing has significant importance in the areas. The main rain is received in the

“kremt “(July-September). On average the area receives a long-term mean annual rainfall of

726mm (LPAR, 2007).

Site 2: Borena

Borena zone is one of the 18 administrative zones of Oromiya Regional State. It is located in

the Southern part of the state (between 3°36′- 6°38′ N latitude and 3°43′- 39°30′ E longitude)

and borders Kenya. Yabello is the capital town of the zone which is located 570 km away

south of Addis Ababa. The zone is divided into 8 districts namely, Gelana, Abaya, Bule Hora

(the previous Hagere Mariam), Borena, Arero, Moyale, Dire and Teltele (Daniel, 2008). The

altitude ranges from 970 masl in the south bordering Kenya to 1693 masl in the North east.

Drought is a common phenomenon in many parts of the zone. Erratic bi‐modal rainfall regime

is prominent in most of the districts. Annual average rainfall ranges from 400mm in the south

to 600mm in the north. The main rainy season is from (March‐May) locally known as

“Ganna” and the short rains from October‐November called “Hagaya”. “Adollasa” season is

24

characterized by dry and cool temperature which occurs between the main rains and short

rainy season. The annual mean temperature ranges from13-28.6 oC (Lasage et al., 2010).

Site 3: Siti

Siti zone is one of the 9 administrative zones of Somali National Regional State. Situating in

the Northern most tip of the region, it bordered with Djibouti in the North, Somalia in the

North-East, Jigjiga Zone in the South-East, Dire Dawa and Oromiya Regions in the South and

Afar Region in the West. It is located between 8°44′- 1°00′ N latitude and 40°22′- 44°00′ E

longitude. Shinille is the largest town of the zone and located 353 km East of Addis Ababa.

The zone has 6 districts namely Aysha, Shinille, Afdem, Dembel, Erer and Meisso (Eshetu,

2003; cited in Amare, 2004).

The altitude in Siti zone ranges from 950 to 1350masl. The annual mean temperature ranges

between 22.5 and 32.5°C, depending on the location within the zone. There are two rainy

seasons, namely “Diraa” or “Gu” (short rain) from mid-March to mid-May and the “Karan

“(long rain) from mid-July to mid-October. The average annual rainfall ranges between 500 to

700 mm (Save the Children UK and Disaster Preparedness and Prevention Agency, 2008).

3.2. Livestock Demography in the Study Areas

In the study areas, particularly in Borena and Siti zones population livelihood mainly depends

on livestock production. Cattle, goat, sheep, camel and donkey are the major livestock species

in the areas. Based on CSA (2013) livestock sample survey report, total numbers of different

livestock by type of animal for Oromiya, South Wollo, Borena and Siti zones are summarized

in Table 7.

Table 7. Total number of livestock by type and zone

Zone Cattle Sheep Goats Horses Mules Donkeys Camels Poultry Beehives

Oromiya 278,789 86,780 164,891 436 - 43,315 14244 265,447 6,416

S.W. 1,564,091 1,948,943 720,700 86,221 29,229 380,608 13,101 1,662,389 112,656

Borena 1,048,909 396,819 989,691 840 2,726 73,224 62,789 556,466 98,829

Siti 21,627 59,482 194,362 - - 9,256 12,333 5,010 22

Source: CSA (2013); S.W. = South Wollo

25

Figure 1. Map of Ethiopia and selected provinces for the baseline survey and performance

monitoring studies

26

3.3. Sampling Strategy

A hierarchical sampling procedure was followed where the big sampling frames were

administrative zones. A rapid informal field survey and discussion with the zonal agricultural

bureau experts was made before the main data collection to know the distribution of the

targeted goat populations in each study areas.

Based on the outcome of the rapid informal field survey and discussion with the zonal

agricultural bureau experts, districts which were accessible, representative and had indigenous

goat production potential were purposively selected. After further discussion with the districts

agricultural development agents and key informants a total of 14 Peasant Associations (PA) (5

in Bati Area; 5 in Siti; 4 in Borena) were selected. During selection of PAs, the distribution

and density of the respective goat types and accessibility were considered.

At the final stage, the lists of households who own at least two adult goats with a minimum of

one year experience in goat husbandry practice were prepared in each PA with the help of PA

development agents and leaders. A total of 345 households (98 from Kalu and Bati, 132 from

Yabello and 115 from Erer and Shinille districts) were selected from the prepared list for

interview using systematic random sampling procedure. Starting from the first, respondents

were selected by a fixed interval until the desired sample size was obtained from each PA in

each district. The selection interval was determined by ratio of total number of listed goat

owners with the number of required respondents (35) per PA.

3.4. Data Collection and Management

3.4.1. Description of production systems

The site selection and the household baseline surveys were conducted from 21 January to 14

March 2013 in Eastern South Wollo and Oromiya administrative zone of Amhara National

Regional State for Bati goats, Borena administrative zone of Oromiya National Regional State

for Borena goats and Siti administrative zone of Somali National Regional State for short-

eared Somalia goats. A checklist and semi-structured questionnaire, prepared by adopting a

questionnaire prepared by International Livestock Research Institute and Oromiya Agricultural

27

Development Bureau for survey of livestock breeds in Oromiya (Workneh and Rowlands,

2004) was used. Some of the questioners were pre-tested with a few households to check

whether it is designed in the way understandable to participants or not. The questionnaire was

administered to the selected respondents by a team of enumerators that spoke the language of

the respondents and trained on methods and approaches on phenotypic characterization of

AnGRs. The data collection teams were composed of researchers from Jigjiga, Sirinka, Debre

Berhan and Yabello agricultural and livestock research centers and experts from zonal and

district offices.

Information on household socioeconomic characteristics, socio-cultural importance of goats,

management practices, breeding system, unique adaptive character, goat feeding and

watering, production constraints and other related issues were collected using semi-structured

questionnaires (Appendix B). Participatory focus group discussions were held with livestock

keepers and key informants to generate additional information regarding the targeted goat

breeds importance and management practices.

Temperature, precipitation, agro ecology and livestock and livestock population demography

of the study areas were collected from published and unpublished secondary data sources

(Kothari, 2004).

3.4.2. Morphometric data collection

Based on breed morphological characteristics descriptor list of FAO (2012) for morphological

characterization of goats, both qualitative and quantitative data were collected from 601 heads

of adult (4pair of permanent incisors) goats comprising 162 Bati (128 females and 34 males),

246 Borena (201 females and 45 males) and 193 Short-eared Somali (139 females and 54

males). However, because of difficulty of finding adequate number of 4PPI males,

measurements were taken from 2PPI and above males. To avoid genetic similarity of goats, 1

to 4 animals per household (based on number of goats) were used for both qualitative and

quantitative traits recording.

28

Discrete or qualitative traits such as: sex, coat color pattern, coat color type, horn presence,

horn shape, horn orientation, ear orientation, facial (head) profile, wattles presence, beard

presence, ruff presence and back profile were recorded. Quantitative traits such as: Body

Length (BL), Chest Width (CW) Height at Withers (HW), Chest Girth (CG), Rump Length

(RL), Pelvic Width (PW), Horn Length (HL), Ear Length (EL) and Scrotum Circumference

(SC) for males were measured using textile measuring tape. Body weight measurements were

measured using suspending balance having 50 kg capacity with 0.2 kg precision in the

morning to avoid the effect of feeding and watering on the animal’s size (FAO, 2012).

Pregnant does were excluded from sampling. Body Condition (BC) scoring was done based

on description of FAO (2012) body condition scoring of goats (Appendix (F).

3.4.3. On-farm flock monitoring and evaluation

Flock monitoring was carried from the beginning of April to end of December, 2013 (9

months). Two PAs for each goat population (Birra and Arabo for Bati, Dahrito and El-Woye

for Borena and Degha-Jebis and Gaad for Short-Eared Somali) were selected for monitoring

activities. A total of 125 household flocks (46 Bati, 48 Borena and 31 Short-Eared Somali)

were involved in the monitoring activity. The targeted goat population possession and

willingness of goat owner to participate in the study were the criteria of selection.

At the beginning of the study (April, 2013), a total of 350 breeding does (113 Bati, 137

Borena and 100 Short-Eared Somali goats) were randomly selected and identified with

numbered plastic ear tags from the selected flocks. However, most of the selected

pastoralists/agro-pastoralists in Siti area were reluctant to continue in flock monitoring

activity fearing body condition loss due to ear tagging and weighting activities.

Consequently, only 11 household flocks growth performance were monitored for Short-eared

Somali goats’ growth performance study. An enumerator trained on how to take records was

recruited in each PA and routinely checked by the representatives from the nearest research

centers.

During the time of monitoring: sex, birth date, type of birth (single or twin), live weight ( at

birth, 30, 90 and 180 days) of kids and parity of dam were recorded under the existing

29

management conditions by recruited enumerators. Birth date, birth weight, type of birth, sex

of kid, and parity of dam were recorded within 24 hours of the new birth.

3.5. Data Analyses

All quantitative and coded qualitative data were entered into Microsoft Office Excel, 2013 for

further analysis using Statistical Analysis System Version 9.2 (SAS, 2008).

Basic statistics (mean, standard deviation, frequency and percentage) for body measurements

such as qualitative and quantitative traits were carried out. Indices were calculated for all

ranking data according to a formula: Index = sum of (3 for rank 1 + 2 for rank 2 + 1 for rank

3) given for an individual attribute divided by the sum of (3 for rank 1 + 2 for rank 2 + 1for

rank 3) for overall attributes. A General Linear Model (GLM) procedure of SAS was used to

analyze the quantitative data of adult goats and growth traits of kids. For morphological

characterization of adult goats, the data were analyzed fitting linear body measurements as

independent variables and goat population as fixed factor whereas the growth performance

traits of kids were analyzed taking sex of kids, type of birth and parity of dam as fixed effects.

The magnitudes of quantitative variables were expressed as Least Square Means (±SE). Chi-

square test was used to test whether there is a significant difference at 5% level of

significance between the observed frequencies in two or more categories and F test was used

to compare means between study areas or populations. Means were separated using Tukey’s

HSD method. The following fixed effect models were used to analyze morphological body

measurements on adult goats and growth traits of kids.

Model I: It was used to analyze quantitative traits of adult goats separately for both sexes

Yij= μ + Bi + εij

Where: Yij = observed quantitative measurement of trait of interest

μ = population mean

Bi = ith goat population effect (i = 1, 2, 3)

εij = random error associated with quantitative body measurements

30

Model II: It was used to analyze growth traits

Yijkl= μ + Si + Pj +Tk+ εijkl

Where: Yijkl = observed live weight and weight gain (Yijklth individual)

μ = Overall mean

Si= the effect due to ith sex (I = 1, 2)

Pj = the effect due to jth parity number (j = 1, 2, 3, 4, ≥5)

Tk= the effect due to kth type of birth (k = single, twin)

εijkl = random residual error associated to Yijklth observation

Pearson’s correlation coefficient was estimated between body weight and other linear body

measurements for each population. This was done separately for the two sexes including

Scrotum Circumference (SC) for males.

The stepwise multiple regression procedure of SAS was used to obtain models for estimation

of body weight from linear measurements. The smaller values of Conceptual predictive (Cp),

Akaike Information Criteria (AIC), Schwarz Bayesian Criteria (SBC) and RMSE and the

higher value of R2 were used to determine those traits that contribute much to the response

variable (Kaps and Lamberson, 2004). The following model was used for the estimation of

body weight from linear body measurements.

Yj = α + β1X1 + β2X2 + . . . + βnXn + ɛj

Where: Yj = the dependent variable; body weight

α = the regression intercept

X1, X2 . . . Xn are the explanatory traits (BC, BL, HW, CG, CW, RL, PW, HL, EL and

SC for males only)

β1, β2, . . . βn are partial regression coefficients of the traits

εj= the residual random error

The quantitative variables from female and male animals were separately subjected to

discriminant (DISCRIM) and canonical discriminant analysis (CANDISC) procedure of SAS

to ascertain the existence of population level phenotypic differences among the goat

31

populations. The stepwise discriminant analysis procedure (PROC STEPDISC) of SAS was

applied to determine which morphological traits have more discriminant power than others.

32

4. RESULTS AND DISCUSSION

4.1. Description of Production Systems

4.1.1. General Household Characteristics

The study households gender, age category and level of education are presented in Table 8.

The percentages of male headed households were 93.88, 68.18 and 79.13 in Bati, Borena and

Siti areas, respectively. The number of female household heads who owned goats in all study

sites was significantly (p<0.05) smaller as compared to male household heads. However,

female household heads at Borena district had relatively higher proportion (31.82%) as

compared with female headed households at Bati and Siti areas. The female household heads

were single mothers either the husband died or they divorced. The small proportion of female

household heads indicated that men play a dominant role in decision making over livestock

production management and the use of benefits from live animal sale.

In Bati area, the average family size (±SE) of the sample households (6.5±0.30) was

significantly (p<0.05) lower than Borena (8.07±0.26) and Siti (7.68±0.26) area, but there was

no significance difference (p>0.05) between Borena and Siti area average family size. The

proportion of goat owners’ aged between 31-40 years was higher across the study areas,

accounting 31.63% in Bati; 24.4% in Borena and 34.78%. It can be conclude that most of the

farmers/pastoralists have productive power in the study area. However, in Borena the

proportion of respondents in the age of 20-30 years old were equally higher with the

respondents between 31-40 years old (24.4%), indicating that goat acquisition in early age is

higher in the area as compared with the other two study areas. This might attribute to the

existence of goat possession culture thorough dowry and kinship.

Different studies in different part of Ethiopia ( Lishan, 2007; Tesfaye, 2009; Tesfaye, 2010;

Grum, 2010) reported that majority of goat owners were unable to read and write. Similarly,

the current study revealed that most of goat owners (>75%) in Borena and Siti areas were

illiterate. Whereas in Bati area, about 37.76% and 18.37% of sampled goat owners were

attending religious and/or adult education and primary education, respectively. This indicates

33

about 56.13% of sampled goat owners in the area were at least able to read and write. This

would be a good opportunity to practice household based performance recording system and

breed improvement interventions.

Table 8. Households’ gender, age category and level of education in the study areas

Descriptor Bati area Borena Siti

N % N % N %

Sex of respondent

Male 92* 93.88 90* 68.18 91* 79.13

Female 6 6.12 42 31.82 24 20.87

X2-value 75.47 17.45 39.03

Age group (years)

<20 3 3.06 4 3.3 4 3.48

20-30 13 13.27 32* 24.24 19 16.52

31-40 31* 31.63 32* 24.24 40* 34.78

41-50 29 29.59 21 15.91 25 21.74

51-60 11 11.22 22 16.67 16 13.91

>60 11 11.22 21 15.91 11 9.57

X2-value 38.04 23.91 40.43

Educational level

Illiterate 43* 43.88 101* 76.52 95* 82.61

Religious and/or

adult education

37 37.76 9 6.82 13 11.30

Primary school(1-8) 18 18.37 20 15.15 7 6.09

Secondary school

(9- 12)

0 0 2 1.52 0 0

X2-value 10.43 191.82 126.12

Family size

(mean ±SE) 6.5±0.30b 8.07±0.26a 7.68±0.26a

*p<0.05; x2 = Pearson Chi-square; N = Number of observation

34

4.1.2. Farming and non-farming activities

The mixed crop-livestock production system is the predominant system (96.94%) in Bati area.

The major crops such as sorghum, maize, teff, sesame, chick pea and pulses are growing

during the short and long rain seasons of the year. Cattle, goat, sheep, donkey and camel are

major livestock species reared in the area (Table 9).

Over 60% of Ethiopian land area is semi-arid lowland, dominated by a livestock economy

(IFAD, 2009). Due to low and highly variable rainfall conditions as well as extreme

temperature, crop cultivation is limited in Borena and Siti areas. As a result, majority of the

sampled households (74.78% in Siti and 52.27% in Borena) reported livestock production as a

main farming activity while the remaining households (47.73% in Borena and 25.22% in Siti)

were practiced crop cultivation in addition to livestock rearing. The main crops that have been

cultivated by Borena agro-pastoralist were maize, teff, haricot been, sorghum, bean and wheat

during the main rainy season “Gaana”. Whereas in Siti area maize and sorghum were the

main crops cultivated and rarely vegetables are also grown when there is enough rain. Similar

findings were also reported by Grum (2010) that the two most cultivated crops in the rural

PAs of Dire Dawa Administration council were maize and sorghum. According to the

information obtained from respondents in Borena crop cultivation is expanding and the

demand to get a plot of land for cropping locally called “obru” is increasing. Due to the

recent trend of the expansion of croplands the respondents have been worried to the future

that the grazing lands to keep animals may shrink. Intensification of the livestock production

system so that the pastoralists can rear livestock in certain plot of land in parallel with food

crop cultivation could minimize the pastoralists’ doubt.

During the slack season (when there is no crop cultivation activity) 32.62 % of the

interviewed farmers in Bati area are participating in off-farm activities such as local livestock

trading (15.31%), daily laborer (11.22%) and hand craft (6.12%). Similarly in Borena, out of

the interviewed households 17.42% were participated on local livestock trading and 6.06%

were as daily laborer along with crop farming activities. In Siti zone, only 5.22% of the

respondents participate in local livestock trading and daily laborer on non-farming activities.

Though local administration at Siti banned making of charcoal and collection of fuel wood for

35

sale, relatively high percentage of respondents (33.04%) were still practiced charcoal making

and fire wood selling which mentioned as one of the cause for having low income, which can

be used to purchase household needs such as feed and other too. Similarly, Beyene (2008)

was reported the main reasons (limited income and seasonal nature of agriculture activities

and large family size) why farmers in rural Ethiopia are participated on off-farm activities..

The contributions of farming and non-farming activities for households’ source of food and

income generation are presented in Appendix Table 1. In Bati area crop production (index =

0.565) ranked first as households food source supplemented by the sale of livestock and

livestock product (index = 0.375). In the meantime, when cash is needed the highest share is

from livestock and livestock product selling (index = 0.549). In both Borena and Siti areas the

highest proportion of households’ food and cash need were derived from livestock sale.

Azage et al. (2009) reported that pastoralists derive over 90% of their cash income from

livestock.

During normal season (when rain is available) some agro-pastoral community of Borena

cultivated crops like maize, sorghum and teff for household consumption (index = 0.470) and

purchase of commodities such as cloth, sugar and animal and human health care besides

livestock rearing. The reported contributions of crop as food source and income generation of

households’ in Siti area were very limited.

4.1.3. Livestock composition and holding pattern

The reported overall average and percentage of livestock species owned per household is

given in Table 9. The major livestock species observed in the study areas were small

ruminants (goats and sheep), cattle, camels and donkeys. Goats were the predominant

population in number across the study areas accounting 72.01% (Siti), 50.93% (Bati) and

47.38% (Borena) of other livestock species. Livestock species which constitute the largest

share in the value of livestock assets of a household are defined as the principal animal (Fredu

et al., 2009). The cause of relatively smaller share of goats in total livestock possession in

Borena might be due to significantly higher (p<0.05) average cattle possession (10.42) than

Bati and Siti areas. The survey result revealed that significant (p<0.05) deviation in average

36

goat possession of households among the study areas. The higher mean (±SE) goat flock size

per household was found in Siti area (44.02±3.33) followed by Borena (23.08±1.94) and Bati

area (8.99±0.59). The reason of lower average number of goat possession of Bati farmers

might be due to the limitation of grazing/browsing area which is happened due to the

expansion of arable land in Bati.

The average number of goats owned per household found in the present study around Bati

area was comparable with the previous study of Tesfaye et al. (2006) who reported 7.79 goats

per household for the same area. On the other hand, the average goat holding per household in

the present study at Siti was relatively higher than the work of Grum (2010) and Sisayet al.

(2006) who reported 34 and 10.08 heads per household for the same goat breed in rural PAs

of Dire Dawa Administration Council and Siti, respectively. This suggested that the existence

of variation in average goat holding per household across the districts, years and seasons as a

result of occurrence of drought and incidences of diseases .

Table 9. Mean (±SE) and percentage of livestock species owned per household

Species

Bati area (N=98) Borena (N=132) Siti (N=115)

Mean ± SE % of other

livestock

Mean ± SE % of other

livestock

Mean ± SE % of

other

livestock

Goat 8.99±0.59c 50.93 23.08±1.94b 47.38 44.02±3.33a 72.01

Cattle 3.94±0.29b 22.33 10.42±1.21a 21.39 1.70±0.26c 2.78

Sheep 1.27±0.22c 7.16 7.82±0.82b 16.05 11.89±1.14a 19.45

Chicken 2.43±0.36a 13.77 3.70±0.49a 7.60 0.16±0.13b 0.26

Camel 0.31±0.07b 1.77 1.64±0.32a 3.37 1.88±0.29a 3.08

Donkey 0.40±0.08b 2.27 0.78±0.17b 1.60 1.47±0.14a 2.40

Beehive 0.31±0.13ab 1.77 1.27±0.49a 2.61 0.01±0.01b 0.07

a, b, c: means with different superscript in the same row are significantly different (p<0.05).

SE= Standard Error

N= Number of respondents

37

4.1.4. Flock structure

The proportion of the different classes of animals reflects the management decision of the

producers which in turn is determined by their production objectives (Solomon et al., 2010).

In this study, as compared to other age groups breeding does made a major share followed by

kids less than 6 months in all areas (Figure 2). The mean (±SE) breeding doe ownership per

household was 3.51±0.91, 9.30±0.78 and 13.30±0.84 in Bati, Borena and Siti areas,

respectively. The higher proportion of breeding females in the flock followed by suckling age

group in all study sites was in agreement with finding of other researchers in Ethiopia

(Tsedeke, 2007; Tesfaye, 2009; Belete, 2009). The higher proportion of adult females than

other age groups across all study areas indicates that practice of retaining females for

breeding. The average goat flock size (44.02) as well as adult females (13.3) and kids less

than 6 months (13.03) owned per household in Siti was significantly higher (P<0.05) than

Bati and Borena areas. However, the proportion of adult females (30.23%) and kids less than

6 months (29.62%) in Siti area were slightly smaller than the contribution of their

counterparts in Bati and Borena. On the other hand, comparing with Bati and Borena areas,

the share of kids between 6-12 months age (23.86%) and intact males older than 1 year

(12.64%) in Siti area were higher in the flock. From this result, it can be concluded that

pastoralists/agro-pastoralists in the area keep weaned kids for a long period of time which

might be attributed to poor growth rate performance of goats.

The contribution of castrates in Siti, Bati and Borena were 3.65%, 3.52% and 0.95%

respectively. The percentage of castrate found in Siti flocks was close to Grum (2010) for

Short-eared Somali goats and FARM-Africa (1996) for Arsi-Bale goats who reported 3.8%

and 3.5% respectively. Relatively, smaller proportion of castrates in Borena goat flocks

indicated that the existence of low practice of buck castration activity in the area as compared

with Bati and Siti areas due to the high demand of intact males by the exporters in the area.

38

Figure 2. Goat flock structures in Bati, Borena and Siti areas

4.1.5. Purpose of goat keeping

Indigenous goat breeds have a wide range of functions that differ from place to place.

Identification of the reasons is prerequisite for deriving operational breeding goals (Jaitner et

al., 2001). Analogous to the reports of other researchers in Ethiopia ((Tsedeke, 2007;

Getahun, 2008; Tesfaye, 2009; Grum, 2010), goat keepers in the present study mentioned

cash income, milk production and meat consumption are important reasons of goat keeping

(Table 10). Many of households in Borena and Bati area ranked income generation as a

primary reason of goat rearing followed by milk production and meat consumption,

respectively. But in Siti area milk production was ranked as a main reason of goat keeping

followed by income generation and meat consumption. Additionally, goats play important

roles in the socio-economy of the societies. This includes saving, for the payment of social

dues, ceremonial feastings, to show wealth strength and skin for home use and sale. None of

the respondent ranked skin as a reason of goat keeping in Siti, but confirming the results of

32.69

18.05

6.69

39.05

3.52

30.75

22.68

5.32

40.3

0.95

29.62

23.86

12.64

30.23

3.65

0

5

10

15

20

25

30

35

40

45

Kids less than 6months

Kids between 6months and 1 year

Intact males olderthan 1 year

Females olderthan 1 year

Castrates

per

cen

tage

in a

flo

ck

Age group

Bati area

Borena

Siti

39

Grum (2010) and FARM-Africa (1996) who reported the traditional uses of skin by the goat

keepers in the area is as water containers locally made from goat skins known as “qerbid”

were observed (Figure 3). According to the respondents, locally made water container from

goat skin is locally appreciated in keeping drinking water cool for a long time.

Besides producing animal products, goats also provide manure to maintain soil fertility in

mixed crop-livestock and agro-pastoral production systems. The use of manure as fertilizer

was ranked only around Bati area with the index of 0.077. In Borena and Siti areas the use of

manure as a fertilizer of cropping land was not mentioned. According to the agro-pastoralist

respondents, since soil fertility is not serious issue in the areas and cropping land is located far

away from the residence simply they disposed it outside the barn.

Figure 3. Locally made goat skin water container (qerbid) in Siti area

40

Table 10. Purpose of goat keeping in the study areas

Ranking

Purpose

Bati area Borena Siti/Shinille

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Source of

income

86 11 17 0.348 92 26 11 0.426 40 60 11 0.356

meat 40 64 12 0.305 2 30 65 0.165 - 19 56 0.134

Milk 2 30 20 0.101 34 54 35 0.309 72 23 13 0.397

Wealth

strength

0 3 2 0.009 6 18 18 0.091 1 2 4 0.016

Ceremony 1 7 29 0.051 0 1 0 0.003 0 0 2 0.003

Manure 0 21 24 0.077 0 0 1 0.001 0 0 0 0

Skin 0 2 4 0.009 0 0 0 0 0 0 0 0

Saving 11 23 3 0.096 0 0 0 0 3 1 8 0.027

Gift 0 0 3 0.004 0 2 0 0.005 0 13 22 0.067

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each purpose divided by sum of (3 X number of household ranked first + 2

X number of household ranked second + 1 X number of household ranked third) for all purpose of keeping goats

in a study site; R= Rank

4.1.6. Herding practices

Mixed species stocking is managing two or more animal species simultaneously. In the

present study, about 45% of households in Bati area practiced mixed-species stocking

(herding goats with sheep, cattle, equine and camel) (Figure 4a) while 17.24% of respondents

reported mixing with sheep only. The remaining 37.76% of respondents herd their goats

separately without mixing with any livestock species. The privatization of communal

grazing/browsing areas for the purpose of better protection and shortage of laborer were

among the reasons for practicing of multi-species grazing system around Bati area. In Borena

and Siti areas the number of households who keep their goats with cattle, equine and camel

were 1.25% and 4.35%, respectively while 96.21% in Borena and 50.43% in Siti area herd

their goats by mixing with sheep (Figure 4b and 4c). The rest 2.27% in Borena and 45.22% in

Siti zone keep their goats separately. Despite the type and number of species mixed with goats

41

in a specific area, the three areas herding system can be characterized as herded mixed species

grazing system.

According to Anderson et al. (2011 mixed species grazing system may be one of the most

biologically and economically viable systems available to producers, especially on landscapes

that support heterogeneous plant species. Although the simultaneous management of more

than one animal species has challenges in management (Animut and Goetsch, 2008),

researchers stated as biological and economic benefits overshadow the challenges. A major

advantage is the better overall utilization of the standing plant, that is, animal species prefer

different plant species and can foster sound landscape management

42

(a)

(b) (c)

Figure 4. Mixed species stocking/herding systems: Bati (a), Siti (b) and Borena (c)

About 7, 38 and 10% of households in Bati, Siti and Borena area, respectively reported flock

mixing with their neighbors’ flocks throughout the year. The rest of households in each area

herded their flock separately from other flocks, except the probability of mixing with the

adjacent flocks at watering points. In Bati area the farmers herded their flock on the private

grazing/browsing land, while Borena and Siti pastoralists/agro-pastoralists herded the flocks

43

on the communal rangelands where flocks are allowed to browse freely. Fear of

communicable diseases and uncontrolled mating were the important reasons of keeping flocks

separately around Borena and Siti. But in Bati area privatization of grazing/browsing area was

the additional reason reported.

4.1.7. Feed resources and feeding practice

4.1.7.1. Feed resources

The ranking of available feed resources in wet and dry seasons of the year by study site are

shown in Table 11. The reported available feed resources utilization slightly varies with study

site and season (dry and wet). The overall reported feed resources were natural shrubs and

bushes, conserved hay and crop residues. Established forage trees such as sesbania

(Sesbania sesban), leucaena (Leucaena leucocephala) and the commonly “kurkura” (Ziziphis

spina-christi) planted on soil conservation structures and stock exclusion areas were reported

source of goat feed used through cut-and-carry system around Bati area. Natural pasture

(shrubs and bushes) were the predominant feed resource in both dry and wet seasons for all

study areas. Most of the respondents stated crop residues were for large animals. Meanwhile,

some of respondents also ranked crop residues as goat feed particularly during dry season

when there is feed shortage. Among the crop residues used sorghum and maize stover were

the prominent.

44

Table 11. Available feed resources during the dry and wet seasons of the year

Ranking

Feed resources Bati Area Borena Siti

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Wet season

Natural pasture 93 2 2 0.831 132 0 0 0.959 115 0 0 1.00

Established

forage trees

1 12 2 0.085 0 0 0 0 0 0 0 0

Conserved

feeds (hay)

1 1 3 0.023 0 2 0 0.010 0 0 0 0

Crop residue 3 5 2 0.061 0 6 1 0.031 0 0 0 0

Dry season

Natural pasture 90 4 3 0.774 123 9 0 0.746 115 0 0 0.885

Established

pasture/forage

1 10 0 0.063 0 0 4 0.008 0 0 0 0

Conserved

feeds (hay)

1 4 3 0.039 6 11 - 0.077 0 0 0 0

Crop residue 2 15 7 0.118 5 31 9 0.166 15 0 0 0.115

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each feed source divided by sum of (3 X number of household ranked first

+ 2 X number of household ranked second + 1 X number of household ranked third) for all feed sources in a

study site

4.1.7.2. Feed shortage and supplementary feeding

Though goats have wide range of plant species browsing and good feed searching habit, feed

shortage during dry season was reported as one of the constraint in all the study sites,

differences were that causes and months of the year when there is feed shortage. Clear

identification of periods of feed shortages is required for effective feed management and

conservation. In the present study, mentioned seasons of feed shortage in Bati, Borena, and

Siti areas cover from January-mid of June, December-March and September-June,

respectively. Within this ranges May, June and February for Bati area; February, March and

January for Borena and February, January and March for Siti area were the most frequently

mentioned months of pick feed shortage (Figure 5).

45

Figure 5. Period of feed shortage across study sites

Different ways of response to feed shortage were listed by the respondents in the study areas.

The major feed shortage resonances include collecting and providing of green leaves and pod

from perennial plants, crop residues (based on availability), collected or stand hay in Bati and

migration of adult and healthy animals in Borena and Siti areas. Due to large flock size in

Borena and Siti areas, suckling kids and milking does were the most likely to be provided

green leaves and pod from perennial plants. The migration of animals can be to relatives in

other area or the family member (mostly adult males) may take the animals to the areas where

better feed and water resources are available. About 55.1% of Bati area owners also reported

additional supplementations such as kitchen and milling residues, homemade grain, local

grain grinding houses remains and oil seed cake “fagullo” based on availability. Very few

(3.8%) goat owners in Borena practice kitchen and milling residues supplementation but

almost none of goat owners in Siti reported such types of supplementation except mineral

(salt) supplementation.

Mineral (table salt) supplementation was reported across all areas and seasons but majority of

the respondents, 69.4% in Bati area, 78.8% in Borena and 62.6% in Siti supplemented their

0

10

20

30

40

50

60

70

80

90

100

Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

Per

cen

tage

of

hou

shold

s

Months

Bati area

Borena

Siti

46

goats during wet season only when there is sufficient amount of feed. The remaining

proportions in each study area supplemented their goats both in dry and wet seasons.

4.1.8. Water resources, watering frequencies and watering point

4.1.8.1. Common sources of water

The availability of different water sources varied between study sites and seasons of the year.

Table 12 presents common water sources reported by respondents in dry season. The

important sources of water comprise traditional hand dug wells, rivers/streams, ponds and

pump water. The most frequently stated water source in Bati area was permanent

rivers/streams (76.53%) followed by pump water, spring, ponds and hand dug wells in order

of importance. The traditional hand dug wells found the most important sources of water

supply in Borena (98.48%) and Siti (87.8%) followed by ponds and rivers/streams,

respectively. Each traditional hand dug well is governed by a complex set of rules and

regulations that are administered by a group of elected community members. Similar to the

study of Belay et al. (2011) in Ginchi watershed, respondents in this survey stated that during

rainy seasons in addition to permanent water sources, temporary water sources (rain water

collected in depression on grazing lands) used irregularly to satisfy the thirst of livestock in

the study areas.

47

Table 12. Common water sources in dry season

Source of water

Bati area Borena Siti

N % N % N %

Traditional hand dug wells 11 11.22 130 98.48 101 87.8

Rivers/streams 75 76.53 0 0 25 21.74

Spring 14 14.29 0 0 15 13.04

Pond 12 12.24 51 52.04 5 4.35

Pump water 17 17.35 2 1.56 0 0

One individual may respond more than one; N= Number of respondents

4.1.8.2. Watering frequencies and distance

Livestock must have free access to plenty of clean, fresh water at all times to be productive.

However, none of the respondents reported adlibitum access of water for livestock across

surveyed areas except in wet season from temporary sources. During the time of the survey

two types of watering system were observed across the three sites. They were watering at

home (kids and sick animals) and taking animals to water source for direct access. Water for

domestic use and home watering of kids and sick animals was fetched using donkey back. As

presented in Table 13 majority of goat owners (>90%) in Bati area watered their goats every

day and few individuals (6.12%) every one day interval. Because of lack of watering points in

Borena most of the owners took their goats to the watering point once in three (50.76%) and

two (46.97%) days. Whereas in Siti area the owners took their goats to the watering point

once in three days (11.30%) and once in two days (58.26%) and every day (30.43%).

Accessibility (distance) and the number of households used per traditional hand dug well were

found to be factors determining frequency of watering. According to Mengistu (2007), Short-

eared Somali goats deprived water for about three days in dry season showed 22% milk production

reduction as compared to goats watered every day. Since watering is an important management

component, researches required to be carried out to see the impact of watering frequency on

productivity of goats in the dry areas.

48

It was found that during the dry season 94.9, 54.55 and 76.53% of interviewed households in

Bati, Borena and Siti area, respectively, have access to water within 5 km distance and 5.10,

45.45 and 23.48% of households in that order should walk over 6 km to find water. The

results revealed that livestock water accessibility is better in Bati area as compared with

Borena and Siti areas.

Table 13. Watering frequency and distance during dry season in the study areas (%)

Particulars Bati area Borena Siti

Watering frequency N % N % N %

Once a day 92 93.88 3 2.27 35 30.43

Once in 2 days 6 6.12 62 46.97 67 58.26

Once in 3 days 0 0 67 50.76 13 11.30

Distance to Watering

point (km)

< 1 43 43.88 13 9.85 33 28.70

1-5 50 51.02 59 44.70 55 47.83

6-10 5 5.10 48 36.36 27 23.48

>10 0 0 12 9.09 0 0

N= Number of respondents

4.1.9. Housing

All of the interviewed respondents in Siti and about 80.3% in Borena shelter their goats in

separated enclosure made of either wooden or thorny bushes without roof across the seasons

(Figure 6). The remaining 19.7% of respondents in Borena used roofed corral. In general,

most of the observed adult goats’ traditional housing systems in Borena and Siti areas do not

protect animals from predation, theft, climate extremes (particularly in rainy season) except

less extent predation protection. This could result low productivity of the animals. Therefore,

the pastoralists should be aware in the role of improved housing in the productivity of goats.

In Bati area all of the respondents reported roofed goat shelter in both dry and wet seasons.

The form of houses differed between households. Fifty two percent of the respondents use

49

separated roofed corral, the remaining 13.27% and 34.69% shelter their goats inside and

adjacent (locally known as “goreno”) to the family house, respectively. Housing goats inside

family house in this area indicates the probability of outbreak of zoonotic diseases and spread

of external parasites.

Figure 6. Traditional adult goats shelter in Siti (a), Borena (b) and Bati (c) areas

All of the respondents in Borena and Siti and most in Bati area (64.29%) housed kids

separately from the adult flock. In the former two sites kids sheltered within well roofed and

walled kids pen, while in Bati area kids separated from the flock and sheltered inside the

c

a b

50

family house. Differences were observed between Borena and Siti area kids pen walling and

roofing materials (Figure 7). For instance, in Borena the pens were constructed suspended

from the ground and walled and roofed with wood materials and covered with cattle dung to

protect kids from predator biting as well as weather extremes. Whereas in Siti the pens could

be walled with stone or wood and roofed with thorny bush. Most of the owners who have

sheep in the three study areas sheltered with goats.

Figure 7. Traditional kids house type in Siti (left) and Borena (right)

4.1.10. Castration

The percentage of households who practiced buck castration and method of castration used

are presented in Appendix Table 2. The proportion of households who practiced castration

and the average age of castration varied from place to place. Nearly all of goat keepers in Siti

(97.39%), above half of Bati area (69.39%) and bellow half of Borena (21.97%) practiced

castration. As explained under section 4.1.4 of this study, the reason for low rate of castration

in Borena area was due to low demand of castrated goats by the livestock exporters.

Above 50% of respondents who castrate their bucks reported traditional method of castration

in all study areas. In Siti and Borena areas bend wooden material locally known as

‘wormatume’ by Somali people and “tuma” by Borena people was used for traditional closed

castration. Whereas around Bati area smooth and round river stone locally known as ‘alello’

51

was used for similar purpose. However, traditional open castration (i.e. removal of tests using

knife) was reported as alternative method in Borena. Similar methods of traditional sheep

castration using the wooden materials were reported by Tassew (2012) and Tesfaye, (2008).

The reported average (±SE) age of castration (years) in Bati area (1.72±0.11) was

significantly (p<0.05) smaller than in Borena (2.2±0.11) which was significantly (p<0.05)

smaller than in Siti (3.17±0.09).

The motivation for the castration of goats across the three surveyed areas was mainly to

improve fattening and reduce bad smell from bucks so that it can fetch better price in local

markets. In addition 9.2% in Bati area; 8.3% in Borena and 52.2% in Siti performed castration

to control pregnancy from unwanted buck.

4.1.11. Trait preferences

Goat owners across the selected areas were highly interested in body size (conformation), fast

growth rate, milk yield, and drought tolerance (adaptability) and disease resistance and

reproduction rate (Table 14). Body size was the most preferred and frequently ranked trait in

Bati (index=0.272) and Borena (index=0.224) areas. In Siti it was ranked next to milk yield

(0.277) equally with growth rate (index=index=0.157). Unlike Siti and Borena areas, in Bati

area goat owners ranked milk yield after body size, growth rate, disease resistance,

reproduction rate and coat color with the index of 0.084. This indicates that around Bati area

goat milk is the least preferred than Borena and Siti areas; as a result goat keepers gave more

weight for cash income generation (meat production/growth) traits than milk yield. This

implies that designing goat improvement strategy in the area should primarily target towards

meat production traits. Whereas, in Borena and Siti areas both meat and milk production traits

are important and should be considered together.

The most important coat color preferences in Bati area for both sexes were brown but plain

white coat color was the most preferred one by both Borena and Siti pastoralist and agro-

pastoralists. Similar to Halima et al. (2012a) observation, black coat color was not preferred

by the producers in all study areas. In general, slight trait preference discrepancies in different

52

areas were observed. Therefore, goat breed improvement intervention program should be

designed considering these differences accordingly.

Table 14. Ranking of goat trait preference of producers

Trait

Bati area Borena Siti

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Body size/

conformation

42 12 6 0.272 48 11 8 0.224 12 28 15 0.157

Reproduction

rate

11 6 27 0.126 11 15 24 0.112 8 16 10 0.097

Milk yield 8 2 20 0.084 15 23 29 0.155 51 15 6 0.277

Growth rate 15 32 7 0.203 16 32 21 0.172 11 21 32 0.157

Coat Color 3 21 11 0.108 7 12 10 0.071 4 7 7 0.048

Disease

resistance

13 7 25 0.136 13 18 15 0.116 14 12 18 0.123

Drought

resistance

2 4 8 0.038 12 14 18 0.106 11 13 20 0.116

Longevity 0 8 2 0.033 6 5 6 0.044 3 2 4 0.028

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each trait divided by sum of (3 X number of household ranked first + 2 X

number of household ranked second + 1 X number of household ranked third) for all traits in a study site; R=

Rank

4.1.12. Breeding management

4.1.12.1. Breeding stock selection

In the present study goat owners’ selection of breeding stock gave more weight for body

conformation and color type than production characteristics. Unfortunately, they cannot tell

much about the future productivity of an animal simply by looking at it. Ideally, selection

should be a combination of visual appraisal and evaluation of performance records.

The proportion of owners who practiced selection by study site is presented in Table 15.

Majority of the respondents across the study areas practiced selection for both breeding males

and females while few of respondents practiced either for females or males only. The rest

very few owners also did not practice selection. Though age is an important factor in the

selection of breeding stock, farmers/pastoralists did not have specific age of selection, simply

53

they select and sale when they are in financial crisis or in need of substantial money and save

the others which they want to be the parents of the next generation. However, according to the

respondents, since males are early maturing there were possibilities to decide which male to

be the replacement sire in earlier age than females.

Table 15. The proportion of producers who practiced breeding stock selection

Selection of breeding

stock

Bati area Borena Sit

N % N % N %

Both male and female 87 88.78 102 77.17 76 66.09

Female only 8 8.16 22 16.67 4 3.48

Male only 1 1.02 5 3.79 28 24.35

No selection 2 2.04 3 2.27 7 6.09

N= Number of respondents

4.1.12.2. Breeding buck ownership and mating system

Half of (50%) goat keepers in Bati and majority of Borena (64.39%) and Siti (83.48% had

their own breeding buck. About 22% of Bati and 7% of Borena goat owners obtained their

breeding bucks from market through purchase and the rest from their own flock/ breeding

stock. It was observed that the average breeding buck and doe ratio was 1:5.3 in Bati, 1.8.6 in

Borena and 1:9.4 in Siti. The result revealed that buck scarcity was not the problem in all

areas. The mean (±SE) number of breeding buck per flock within the interviewed households

was 0.66±0.12, 1.08±0.11 and 1.42±0.11 for Bati, Borena and Siti areas, respectively. This

showed that the existence of more than one breeding buck ownership custom across the study

sites. Reserve for the death of main buck, large flock size, demonstration of wealth

accumulation, socio-cultural purposes were among the major reasons raised by the

respondents for keeping more than one breeding buck in a flock. Because of the presence of

large number (50%) of households who did not have own breeding buck in Bati area, the

average breeding buck per household was smaller as compared with Borena and Siti area goat

owners. This might be due to the extensive castration and fattening practice in the area. The

54

extensive castration practice could reduce problem of inbreeding and pregnancy from

uncontrolled mating. On the other hand, early age castration may lead to scarcity of bucks in

the flock.

About 50% Bati area, 35.61% Borena and 16.52% Siti goat producers who do not have

breeding buck stated that they tend to borrow neighbor buck or mating took place at random

with bucks present in the flocks in communal browsing area and watering point. Very few

owners in Bati area (4.08%) were used communal (group) bucks given by extension office.

In the present study, in all the three areas uncontrolled natural mating system was surpassed

while controlled natural mating (using breeding bucks individually) was very unpopular

(Table 16). According to Kosgey (2004), an advantage of natural uncontrolled mating is that

it allows for all year round breeding. On the other hand, uncontrolled mating together with

small flock sizes and poor/absent record keeping on pedigree are expected to result in severe

inbreeding which leads to poor growth rates (Saico and Abul, 2007).

Table 16. Type of natural mating systems

Natural mating

system

Bati area Borena Siti

N % N % N %

Controlled 11 11.22 2 1.52 2 1.74

Uncontrolled 87 88.78 130 98.48 113 98.26

N= Number of respondents

4.1.12.3. Breeding buck management and duration in the flock

Even though the impact of high-quality bucks in extensive goat production system is low due

to uncontrolled natural mating practice, in Bati area about 44.9% of buck owners give

additional supplements such as homemade grain, kitchen and food residues and sometimes

purchased concentrates. Very fewer breeding buck keepers in Borena (7.06%) and Siti

(6.25%) areas also provide special management for their breeding bucks. Therefore,

investment in breeding bucks was not common in these areas. There was a significance

(p<0.05) difference in duration (years) of bucks in a flock across the study areas. As shown in

55

Table 17, Borena and Siti goat producers kept bucks for a long period of time in a flock.

According to Jimmy et al. (2010), such long duration depicts non quantifiable inbreeding in a

flock.

Table 17. Bucks’ average years of service recalled by owners

Study site Mean ± SE Minimum Maximum

Bati area (N=47) 2.35±0.11c 1 4

Borena (N=85) 4.91±0.15b 2 8

Siti (N=96) 5.81±0.21a 2 10

a, b, c means with different superscript are significantly different (P<0.05); N=Number of respondents, SE

=Standard Error

4.1.12.4. Breeding doe selection criteria

Table 18 summarized ranking of the owners’ selection criteria for breeding does in the three

surveyed areas. Siti pastoralist/agro-pastoralists were concerned more about milk production

potential of does (index=0.374) followed by body size/conformation and litter size with the

indices of 0.279 and 0.224, respectively. Unlike Siti pastoralist/agro-pastoralists, Borena

pastoralist/agro-pastoralists ranked milk yield 2nd with the index of 0.214 next to body

size/conformation (index = 0.314) followed by coat color (index = 0.174) and kid survival

(index= 0.140), while in Bati area milk yield was ranked 4th with the index of 0.133 next to

body size/conformation (index = 0.313), coat color (index = 0.207) and litter size (index=

0.182).

56

Table 18. Ranking producers selection criteria for breeding doe in the study areas

Selection

criteria

Bati area Borena Siti

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Color type 13 28 22 0.207 13 41 25 0.174 1 2 0 0.016

Body size/

conformation

41 21 10 0.313 59 27 25 0.314 26 13 17 0.279

Kid survival 3 2 8 0.037 1 2 4 0.14 0 1 0 0.004

Paternal history 1 2 2 0.016 1 0 1 0.009 0 0 2 0.005

Maternal history 1 2 8 0.027 12 6 15 0.073 1 3 10 0.044

Age at 1st

sexual maturity

0 4 1 0.016 0 0 1 0.001 0 2 3 0.016

kidding interval 1 3 5 0.025 0 0 0 0 2 2 4 0.033

Litter size 16 19 17 0.182 7 11 19 0.074 7 23 30 0.224

Milk yield 15 11 8 0.133 26 34 32 0.214 34 25 8 0.374

Temperament 2 2 5 0.023 0 0 1 0.001 0 2 0 0.005

Horn presence

and shape

0 1 3 0.009 0 0 0 0 0 0 0 0

Adaptability 1 1 2 0.012 0 0 0 0 0 0 0 0

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each selection criteria divided by sum of (3 X number of household ranked

first + 2 X number of household ranked second + 1 X number of household ranked third) for all selection criteria

in a study site; R= Rank

4.1.12.5. Breeding buck selection criteria

Buck is the most important animal in the flock. It contributes 50% of the genetic makeup of

kid born and determines overall pregnancy rate of the flock. The choice of good breeding

buck is an important factor and fundamental in goat production. As indicated in Table 19,

characterstics like conformation, growth rate, coat color, libido, maternal history were

considered as important in all of the study areas and given due emphasis in selecting breeding

buck.

57

Table 19. Ranking producers’ selection criteria for breeding buck in the study areas

Selection

criteria

Bati area Borena Siti/Shinille

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Color type 33 27 21 0.330 11 40 50 0.244 3 17 22 0.107

Conformation 48 29 7 0.396 67 21 19 0.394 51 30 11 0.368

Fertility 0 4 6 0.027 0 0 1 0.001 0 5 8 0.030

Paternal

history

1 0 0 0.006 0 0 4 0.006 1 3 8 0.027

Maternal

history

1 0 6 0.017 2 2 7 0.025 8 23 18 0.145

Libido 2 0 3 0.017 4 5 3 0.037 14 4 23 0.120

Growth rate 6 25 26 0.178 25 42 28 0.289 24 20 7 0.196

Adaptability 0 2 3 0.013 0 0 0 0 0 0 0 0

Horn presence

and shape 0 1 7 0.016 0 0 2 0.004 0 1 2 0.007

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each selection criteria divided by sum of (3 X number of household ranked

first + 2 X number of household ranked second + 1 X number of household ranked third) for all selection criteria

in a study site; R= Rank

Th body conformation of breeding buck ranked first by all Bati, Borena and Siti goat owners

with an index values of 0.396 , 0.394 and 0.368, respectively. In Bati area next to body size;

coat color, growth rate and fertility was ranked as the most important, while sexual desire,

growth rate and coat color type in Borena; and growth rate, maternal history and sexual

desire for Siti received the higher index next to body size in order of appearance.

Generally the utilization of physical and performance characteristics as a selection criteria by

the households revealed that the selection decision made by them followed stepwise mode i.e.

the first screening is based on physical appraisal in early stage and further selections are based

on production and reproduction characteristics at matured stage (after first kidding for females

and mating for males).

58

4.1.13. Reproductive performances

The age at sexual maturity of male goats at Bati, Borena and Siti areas were found to be

8.21±0.28, 9.49±0.27and 13.43±0.45 months, respectively, in the meantime female goats were

first mated at age of 8.77±0.23, 10.13±0.27 and 14.83±0.45 months in that order (Table 20). The

average age at puberty was significantly (p<0.05) different for both sexes across the three

study sites being the lowest in Bati area. The variation might be due to breed, availability of

forage, environment and presence of buck in the flock (for females).

The age at first kidding for Bati, Borena and Siti area goats averaged at 14.98±0.24, 15.86±0.22

and 20.15±0.12 months old, respectively, which was statistically (p<0.05) higher for Siti area

but for Bati and Borena areas did not have significance difference. The present findings on

Bati area was comparable with the report of Endeshaw (2007) and Rume et al. (2011) who

reported 14.88±0.3 and 14.25±0.69 months age at first kidding for Arsi-Bale (Loka Abaya in

Ethiopia) and Patuakahli (Bangladesh) goat types, respectively. But Tsedeke (2007) and

Belete (2009) reported smaller age at first kidding for Arsi-Bale (12 months) and Keffa (12.5

months) goat types, respectively. Age at first kidding in Siti area found in the present study

was close to the report of Grum (2010) who reported 19.9 months for the same goat type.

Alexander et al., (1999) stated that reproductive characteristics including age at first kidding

are influenced by many factors such as the genetic makeup of an individual, physical

environment, nutrition and time of birth.

According to the respondents in Bati, Borena and Sit, area breeding does can serve in the

flock for 8.02±0.23, 8.44±0.18 and 10.2±0.17 years, kidding in average every 7.95±0.19,

8.42±0.17 and 8.81±0.18 months, respectively. For the corresponding areas mean (±SE) of

11.08±0.25, 9.77±0.15 and 9.04±0.16 kidding per life time of a doe were reported. The

inverse relation of average life time service and number of kidding per life time of a doe in

the studied areas indicates goats around Bati area have better reproduction performance than

goats in Borena and Siti area which might be attributed to either genetic and/or management

variation.

59

Table 20. Some reproductive performances as estimated by respondents

Characters Bati area Borena Siti

Mean±SE Range Mean±SE Range Mean±SE Range

Age at 1stsexual

maturity males

(months)

8.21±0.28 c 6-18 9.49±0.27b 6-20 13.43±0.45a 6-30

Age at 1stsexual

maturity females

(months)

8.21±0.28 c 6-18 10.13±0.27b 6-24 14.83±0.45a 6-30

Age at1st kidding

(months)

14.98±0.24b 12-24 15.86±0.22b 12-24 20.15±0.12a 12-36

Kidding interval

(months)

7.95±0.19b 6-12 8.42±0.17ab 6-12 8.81±0.18a 6-12

Average reproductive

life time (years)

8.02±0.23b 4-13 8.44±0.18b 5-15 10.2±0.17a 8-17

Number of kidding/

life time /doe

11.08±0.25a 8-18 9.77±0.15b 6-15 9.04±0.16c 5-13

a, b, c: means with different superscript in the same row are significantly different (p<0.05); Min. = Minimum,

Max. = Maximum, SE =Standard Error

4.1.14. Goat milking

In the present study higher percentage of respondents in Siti (98.26%) and Borena (94.70%),

and below half of the respondents around Bati area (28.57%) reported goat milking and

consumption (Table 21). This result also reflected that the consumption of goat milk is

surpassed in pastoral areas of the country. Therefore, there is more practical significance to

research and promote the goat milk nutritional content and acceptability in other goat

producing areas of the country. All of the respondents use goat’s milk for household

consumption except Siti pastoralists who reported sale of goat milk during the wet season

when there is more milk yield which exceeds from household consumption. According to the

respondents boiled goat milk alone or with tea principally given to children and sick

household members as a medicine and then if there is extra the other household members will

access it.

Milk utilization, milking frequency and average lactation length (days) of goats in each study

site are summarized in Table 21. From the report of interviewed participants, frequency of

60

milking was dependent on mode of milking in the household and feed availability (season).

Some owners milked their does in the morning and left the afternoon milk for the kids, the

others who reported milking twice a day milked only one teat during time of milking and left

the second for the kids to suck. As is, frequency of milking based on feed availability could be

either only in the morning during dry season and twice during wet seasons or only in the

morning both in wet and dry seasons (Table 21). Despite the availability of feed, very few

respondents in Borena and Siti (11.54 and 5.26%, respectively) and over 40% in Bati area

stated morning and dusk milking in both seasons and some others only wet season milking.

As shown in Table 21 disparities observed in lactation length of the three areas. The reported

mean (± SE) lactation length of goats in Bati, Borena and Siti areas were 81.43±5.10, 64.44±2.12

and 100.62±2.31days, respectively. These variations might be due to the availability of other

milking livestock (cow and camel) for households, physical environment and type/breed of

goats.

Table 21. Milk utilization, milking frequency and lactation length (days)

Bati area Borena Siti

Parameter N % N % N %

Do you use goat’s milk?

Yes 28 28.57 12

5

94.7 113 98.26

No 70 71.43 7 5.3 2 1.74

Frequency of milking in

wet season

Once per day 13 46.43 42 33.6 5 4.42

Twice per day 15 53.57 83 66.4 108 95.58

Frequency of milking in

dry season

Once per day 12 54.55 23 88.46 54 94.74

Twice per day 10 45.45 3 11.54 3 5.26

Lactation length

(mean ± SE)

28 81.43±5.1b 12

5

64.44±2.12c 113 100.62±2.31a

a, b, c: means with different superscript in the same row are significantly different (P<0.05); N= Number of

respondents, SE =Standard Error

61

4.1.15. Producers perception on some adaptability traits of their goats

In the present survey most of the goat keepers in all the study areas stated that their indigenous

goat types had good level of drought, heat and feed shortage tolerance adaptive traits combination.

On the other hand, high percentage of respondents (76.29, 91.67, 93.04% for Bati, Borena, Siti

areas respectively) reported that their goats had low level of cold tolerance capability (Table 22).

Both Borena and Siti respondents showed similarities by suggesting medium level of disease

resistance and external parasite tolerance of their goats, while Bati area participants perceived

good level of disease resistance and external parasite tolerance.

Finally, the perception of goat owners in this study implied that the goat populations in the

respective studied areas have developed varied adaptable characteristics to be able to survive

and reproduce in those environments. Thus, perceptions’ of producers about adaptive traits of

their animals in those environments should be supported with genetic analysis studies. So that

it can be exploited for future climate change adaptation breeding programs for these

communities.

Table 22. Percentage of respondents in leveling goats’ adaptive trait by study area

Tolerance

Bati area Borena Siti

Good Med. Less Good Med. Less Good Med. Less

Disease 47.42 44.33 8.25 13.64 72.73 13.64 27.83 53.04 19.13

External

parasite

51.55 38.14 10.31 25.00 65.91 9.09 9.57 74.78 15.65

Heat 65.98 27.84 6.19 65.91 34.09 0 65.22 33.91 0.87

Frost/cold 3.09 20.62 76.29 0.76 7.58 91.67 0 6.96 93.04

Drought 53.61 44.33 2.06 69.70 28.79 1.52 54.78 44.35 0.87

Feed

shortage

52.04 46.39 4.12 67.42 31.82 0.76 60.00 33.91 6.09

Water

shortage

30.85 53.19 15.96 86.36 13.64 0 28.70 45.22 26.09

Good= No significant body condition loss and death; Med (medium) = to some extent body condition loss and

death of animals; Less = high body condition loss and death

62

4.1.16. Marketing

As to many other locations of the country, farmers/pastoralists in the studied areas sold their

animals at local markets throughout the year in times of cash need as well as feed shortage.

The meat demand grows much higher during major holidays/festivals. Thus, the density of

producers who sale their goats targeting the particular holidays/festivals was higher. This was

to reap maximum benefit from sales. As stated by the respondents, local household

consumers/breeders, butchers, small traders, brokers (Delalas) and permanent traders or

exporters (particularly around Bati and Borena markets) were the major market participants.

This result was similar with the reports of Tsedeke (2007), Belete (2009) and Tesfaye (2009)

in Southern, Western and Northern part of Ethiopia, respectively.

Shinille, Erer and Dire Dawa; Beke, Yabello and El-Woye; Bati and Gerba are among the

local market places where the Siti, Borena and Bati area farmers/pastoralists sold their goats

respectively. During the time of survey weigh based marketing practice was observed in

Borena and Bati area local markets.

Even though, there is great demand for Bati goats (locally known as “Habesha”) by local

consumers, big traders (exporters) focused on Afar goats found in Bati area, despite their

small body frames as compared with Bati goats. This clearly indicated that the demand for

Bati goats by oversea consumers is low as compared with Afar goats. So that further meat

quality analysis study and comparison of the two goat types will have paramount importance

in designing breeding strategy which considered the preference of oversea consumers and

domestic markets to. In accordance with the reports of Endeshaw (2007), Tsedeke (2007) and

Belete (2009) in Ethiopia and Kosgay (2004) in Kenya, in local markets of Siti and Dire

Dawa informal goat marketing practice (eye ball price setting) was noted. It is also an

indication of less involvement of big traders (exporters) in this areas and loud the requirement

of value chain approach (interaction of different actors at different phases).

Farmers and pastoralists/agro-pastoralists do not have specific age of selling rather simply

they sold their animals whenever they need cash. Nonetheless, the interviewed individuals

were asked to tell the average months when the male and female goats reached for market.

The mean (±SE) age of marketing in Bati male (6.21±0.23 months) and female (6.35±0.23

63

months) goats were significantly (p<0.05) lower than that of Borena and Siti goats. There was

no significance (p>0.05) difference between Borena and Siti area goats’ age of marketing.

The average age of marketing around Borena area was 8.58±0.24 months for males and

8.84±0.22 months for females. The corresponding figures at Siti were 8.35±0.19 and

8.62±0.19 months, respectively.

The selection decision of producers for sex and/or age category of goats for sale determined

by the amount of cash needed and its urgency, market demand and the availability of different

age categories in the flock. The most targeted four category of goats in order of importance

include the following: weaned males, castrates, old does and weaned females in Bati area;

weaned males, old does, old bucks and weaned females in Borena; and castrates, weaned

males), old does and old bucks in Siti (Appendix Table 3).

4.1.17. Animal health management

Based on physiological symptoms, producers were asked to report the occurrence of different

diseases. All of the interviewed producers across the study areas reported the incidence of

symptoms commonly associated with several economically important goat diseases;

depression, circling, accidental death, abortion, coughing, serious nasal discharge which block

nostrils, bloody and bad odor diarrhea, lameness, mouth inflammation, formation of vesicles

on mouth and foot, nodules on the lips and eyes, skin irritation and scratching with fixed

objects were among reported symptoms.

It was found that about 69.79, 55.17 and 69.61% of interviewed households in Bati, Borena

and Siti areas, respectively, have veterinary service access within 5 km distance and 30.21,

44.83 and 30.39% of households in that order should walk over 6 km to find veterinary

service. The most commonly used veterinary services around Bati area were government and

privet clinics while in Borena and Siti area producers have additional service from NGOs and

CAHWs (Table 23).

Even though over 87% of producers across study areas had different veterinary service access,

62.24% of Bati area, 75.76% of Borena and 92.11% of Siti producers reported utilization of

traditional prevention and treatment by traditional healers following the manifestation of the

64

above symptoms either together with the modern veterinary medications or alone; as such the

effective doses of traditional medicines are not fully known, nor the effectiveness, safety and

toxicity. Branding of the swollen body part of animal, medical plants extract dosing,

fumigation, releasing blood and external application of oil, gas, used motor engine oil and

soot were most frequently mentioned traditional mode of disease prevention and treatments.

Similar traditional mode of disease prevention and treatments methods were reported in

Zimbabwe (Homman et al., 2007).

Table 23. Types of veterinary services accesses in the study areas

Type of veterinary

service accesses

Bati area

(N=98)

Borena

(N=132)

Siti (N=115)

N % N % N %

Government clinics 96 97.96 80 68.96 54 52.41

Privet clinics 15 15.63 29 21.97 9 8.73

NGOs 0 0 3 2.62 22 21.35

CAHWs 0 0 22 18.96 54 52.41

N.B One respondent may have more than one veterinary service access; N = Number of respondents; CAHWs =

Community Animal Health Workers; NGOs = None Governmental Organizations

4.1.18. Constraints associated with goat keeping

The important goat production constraints reported by producers across the study areas

summarized in Table 24. Thought the major constraints facing goat breeding systems are

mostly similar, their importance varied across the study areas. Around Bati area feed shortage,

disease occurrences and drought ranked 1st, 2nd and 3rd as major goat rearing constraints whilst

disease occurrences, feed shortage and recurrent drought in Borena; and recurrent drought,

disease occurrence, feed as well as water shortage in Siti area had been perceived by the

respondents as most influencing constraints in order of importance. Both privet and

communal grazing/browsing area scarcity and erratic rainfall contributed for feed shortage in

Bati area, while recurrent drought in Siti and Borena areas. Bush encroachment (Prosopis

juliflora) was also mentioned as additional cause of feed shortage in Siti. Improved rangeland

management can be one alternative to minimize feed shortage by resorting and increasing the

productivity of degraded natural grazing/browsing areas. To control extensive

65

grazing/browsing land utilization integrating traditional leadership and formal administration

are essential. For instance, local by-laws implemented around Bati area for the utilization of

some communal grazing/browsing areas were appropriate and could have positive impact in

livestock productivity and have to be adopted as a role-model even beyond Bati area.

Table 24. Goat production constraints as perceived by the respondents

Main

constraint

Bati area Borena Siti

R1 R2 R3 Index R1 R2 R3 Index R1 R2 R3 Index

Drought 13 39 19 0.237 17 40 55 0.234 60 26 17 0.359

Feed

shortage

46 21 14 0.338 26 60 38 0.296 20 41 28 0.245

Water

shortage

0 3 5 0.019 5 11 16 0.067 17 6 28 0.131

Disease 26 20 31 0.260 84 18 14 0.379 19 43 31 0.251

Predator 4 4 7 0.047 1 4 7 0.023 0 2 2 0.009

Market 0 3 0 0.010 0 0 1 0.001 0 0 3 0.004

Labor

shortage

10 7 7 0.089 0 0 0 0 0 0 1 0.001

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) give for each constraint divided by sum of (3 X number of household ranked first + 2

X number of household ranked second + 1 X number of household ranked third) for all of the constraints for a

production system; R= Rank

Predator, market and labor problem were among the minor reported as goat raising constraints

by all communities. However, predator problem and labor shortage received a little higher

proportion around Bati area as compared with Borena and Siti areas. In all areas, almost all of

the respondents did not rank lack of appropriate genotype/breed as a constraint. This may

suggest that producers have good perception about their indigenous goats’ adaptability and

productivity characteristics and/or it might be due to lack of awareness about improved

breeds. Therefore, since the producers in all study areas are traditional goat keepers, they need

to be aware on the merits of improving local goats before implementations of breed

improvement programs. In the present study, ranking of goat rearing constraints (indices) by

the producers reflected that their priority needs for support services. Hence, stakeholders

should give diligent attention for the problems based on their prioritization to be welcomed by

them.

66

4.1.19. Major goat health problems

In the present study, it is indicated that (Table 24), disease is among the important goat

production bottlenecks as reported by goat owners. Therefore, to adopt adequate health

management strategies, it is fundamental to identify causes of morbidity and mortality and to

investigate the prevalence of diseases by type and dynamics (Chiejina et al., 2002). Existing

health problems were identified and ranked by the respondents; and translated to their

veterinary equivalents with the support of animal health workers in the respective area (Table

25). Similar range of disease problems were reported in Ethiopia (Tesfaye, 2009; Grum, 2010;

Dereje et al., 2013) and most Sub-Saharan countries (Kusiluka and Kambarage, 1996). The

reported health problems were mange mite, pneumonia, pasteurellosis, anthrax and goat pox

were the first five goat diseases identified around Bati area, while contagious caprine

pleuropneumonia (CCPP), coenurosis, pasteurellosis, mange mite and diarrhea in Borena; and

babesiosis, diarrhea, CCPP, goat pox and Pest des Petit Ruminants (PPR) in Siti area were

prioritized by the interviewed respondents. The prioritization of goat diseases by the

respondents in each area revealed that some diseases do not have the same importance across

the study areas. This local variation in health problems indicated the need of area specific

animal health improvement strategy interventions (Homann et al., 2007).

Due to the thicker, highly flexible and clean inner surface features, goat skins from the

highlands of Ethiopia are categorized as “Bati-genuine” and those from the lowlands as “Bati-

type” in the international market (Mahmud, 2000). Nevertheless, Mange mite (locally known

as “Keto”) was the major goat health problem around Bati area. The prevalence of mange

mite in the area will be resulted deterioration of the quality of skin, leather and leather

products; in turn it will drop foreign exchange earnings from skin, leather and leather product

export. Therefore, the government should strengthen community ownership dipping and

spraying facilities in the area.

67

Table 25. Ranking of major goat health problems as reported by goat producers

Location Vernacular name Common name Rank1 Rank2 Rank3 Index

Bati area

Keto Mange mite 71 8 3 0.603

Sal (Gunfan) Pneumonia 10 12 3 0.148

Neft Pasteurellosis 6 13 1 0.117

Dengetegna Anthrax 1 10 3 0.068

Abdra Goat pox 2 4 3 0.044

Bosek Black leg 0 3 2 0.021

Borena

Sombesa CCPP 77 36 8 0.408

Qulda ,Silisa re’e Pasteurellosis 1 28 38 0.127

Sirgo Coenurosis 51 53 14 0.358

Haddo Liver disease 0 4 10 0.024

Albati re’e Diarrhea 2 3 9 0.028

Cito Mange mite 1 12 2 0.038

Selesa Brucellosis

(Abortion)

0 3 1 0.009

Chirmale Anthrax 1 1 1 0.008

Siti

Sogudud Babesiosis 48 22 10 0.400

Gedanod Goat pox 7 19 10 0.139

Sombob CCPP 3 19 15 0.125

Abeb FMD 0 3 9 0.030

Shuben (Xar) Diarrhea 17 17 17 0.206

Candugal PPR 7 2 9 0.069

Ampbar (Cadho) Mange mite 1 3 6 0.030

Index= sum of (3 X number of household ranked first + 2 X number of household ranked second + 1 X number

of household ranked third) given for each type of disease divided by sum of (3 X number of household ranked

first + 2 X number of household ranked second + 1 X number of household ranked third) for all types of diseases

in a study site; CCPP=Contagious Caprine Pleuro Pneumonia, FMD= Mouth and Foot Disease, PPR= Pest des

Petit Ruminants

68

4.2. Phenotypic Description of Bati, Borena and Short-Eared Goat Populations

4.2.1. Qualitative characteristics

The frequency and their percentage of qualitative traits of Bati, Borena and Short-eared

Somali goat populations for both buck and does are presented in Table 26. The observed

overall coat color patterns for both sexes were 64.20% plain, 33.33% patchy/pied and 2.47%

spotted in Bati; 72.36% plain, 23.98% patchy/pied and 3.66% spotted in Borena; and 45.08%

plain, 39.90% patchy/pied and 15.03% spotted in Short-eared Somali goat populations.

Tesfaye et al. (2006) reported higher proportion (93%) of plain coat color pattern for central

highland goats around South Wollo (Bati) and North Shewa (Shewa Robit and Ankober).

Plain brown (dark and light) (51.85%) were the predominant coat colors observed in Bati

goats of both sexes while white coat color were most frequently observed in Borena

(71.54%) and only 36.27% in Short-eared Somali goat populations. In studied sample

populations white mottled with different colors (dark or light red, black), uniform black and

gray color animals were present with small and varied frequencies across populations. Though

the frequencies of some coat colors were small in a population, the current study

demonstrated that the studied goat populations have a wide range of coat colors. Similarly

Halima et al. (2012a) and Grum (2010) reported wide range of coat colors for different

Ethiopian goat populations. The small proportion of black coat colored goats (absent in

males) in sampled populations confirmed the response of producers discussed under section

4.1.13 of this study.

Most of the Bati goats (87.5% females and 67.7% males) had straight head profile and about

14% (11.7% females and 23.5% males) of this goat type were with slight concave head.

Almost all (99%) of male and female Borena goats had straight head profile. From the total

sampled Short-eared Somali goats, 41.7 % females and 77.8% males had straight head profile.

As compared with Bati and Borena goats the frequency of slightly concaved head goats was

higher (48.2%) in Short-eared Somali goats. In studied populations the horned goats (does and

bucks) accounted 94.4, 78.9 and 80.8% in Bati, Borena and Short-eared Somali populations,

respectively. The reminder proportions in each sampled population, except 8.9% of Borena

does which displayed some rudimentary horns, were polled. The proportions of polled bucks

were higher than does in each population across the three populations. This might be due to

69

either producers’ interest in polled bucks or the higher frequency of short-horned allele (HoP)

for males. In horned goats different horn shapes (straight, curved and spiral) and orientations

(backward, forward, upward and lateral) were observed. However, goats with straight horn

shape (96.7% Bati, 68.7% and 54.5% Short-eared Somali) and back ward orientation (71.9%

Bati, 50% Borena and 61.5% Short-eared Somali) were dominant in all populations.

The majority of Bati and Borena goats were characterized by lateral/sideway ear orientation

accounting a total of 59.9 and 78.9%, respectively, followed by hanged down ears observed

in 35.8 and 12.5% of individuals in that order. Very small proportion of goats (4.3% Bati and

7.7% Borena) was also with forward erected ears. Large proportion (> 84 %) of forward and

small proportion (15%) of lateral ear orientations distinguished Short-eared Somali goats from

the two populations. Though straight back profile was predominant in the three goat

populations, other back profiles such as slops up towards the rump, slops down from the

wither and dip were noted rarely.

70

Table 26. Frequency (N) and percentage in brackets for each level of qualitative traits by goat population

Traits

Class level

Bati Borena Short-eared Somali

Female

N (%)

Male

N (%)

Total

N (%)

Female

N (%)

Male

N (%)

Total

N (%)

Female

N (%)

Male

N (%)

Total

N (%)

Coat

pattern

Plain 85(66.41) 19(55.88) 104(64.2) 144(71.64) 34(75.56) 178(72.36) 57(41.01) 30(55.56) 85(45.08)

Patchy/pied 39(30.47) 15(44.12) 54(33.33) 48(23.88) 11(24.44) 59(23.98) 54(38.85) 23(42.59) 77(39.90)

Spotted 4(3.13) - 4(2.47) 9(4.48) - 9(3.66) 28(20.14) 1(1.85) 29(15.03)

Coat

color

type

White 12(9.38) 6(17.65) 18(11.11) 140(69.68) 36(80.00) 176(71.54) 42(30.22) 28(51.85) 70(36.27)

Dark red/brown 40(31.25) 8(23.53) 48(29.63) 1(0.5) 0 1(0.41) 5(3.60) 1(1.85) 8(4.15)

Black 4(3.13) 0 4(2.47) 0 0 0 7(5.04) 1(1.85) 6(3.11)

Gray 1(0.78) 0 1(0.62) 5(2.49) 0 5(2.03) 11(7.91) 2(3.70) 13(6.74)

Light red 30(23.44) 6(17.65) 36(22.22) 2(1.00) 0 2(0.81) 9(6.47) 2(3.70) 11(5.70)

White +Brown 15(11.72) 3(8.82) 18(11.11) 4(1.99) 0 4(1.63) 1(0.72) 4(7.41) 5(2.59)

White +Black 3(2.34) 3(8.82) 6(3.7) 14(6.97) 3(6.67) 17(6.91) 30(21.58) 11(20.37) 41(21.24)

White+ Light brown 23(17.97) 8(23.53) 31(19.14) 35(17.41) 6(13.33) 41(16.67) 34(24.46) 5(9.26) 39(20.21)

Facial

profile

Straight 112(87.5) 23(67.65) 135(83.33) 199(99.00) 45(100) 244(99.19) 58(41.73) 42(77.78) 100(51.81)

Slightly concave 15(11.72) 8(23.53) 23(14.2) 1(0.50) 0 1(0.41) 81(58.27) 12(22.22) 93(48.19)

Slightly convex 1(0.78) 3(8.82) 4(2.47) 1(0.50) 0 1(0.41) 0 0 0

Horn Present 126(98.44) 27(79.41) 153(94.44) 163(81.09) 31(68.89) 194(78.86) 128(92.09) 28(51.85) 156(80.83)

Absent 2(1.56) 7(20.59) 9(5.56) 16(7.96) 14(31.11) 30(12.2) 11(7.91) 26(48.15)) 37(19.17)

Rudimentary 0 0 0 22(10.96) 0 22(8.94) 0 0 0

Horn

shape

Straight 124(98.41) 24(88.89) 148(96.73) 107(65.24) 27(87.1) 134(68.72) 64(50.00) 21(75.00) 85(54.49)

Curved 1(0.79) 3(11.11) 4(2.61) 51(31.1) 3(9.68) 54(27.69) 54(42.19) 1(3.57) 55(35.26)

Spiral 1(0.79) 0 1(0.65) 6(3.66) 1(3.23) 7(3.59) 9(7.03) 6(21.43) 16(10.26)

71

Table 26. (Continued)

Variable

Class level

Bati Borena Short eared Somali

Female

N (%)

Male

N (%)

Total

N (%)

Female

N (%)

Male

N (%)

Total

N (%)

Female

N (%)

Male

N (%)

Total

N (%)

Horn

orie-

ntation

Lateral 0 0 0 30(18.18) 2(6.45) 32(16.33) 9(7.03) 4(14.29) 13(8.33)

Up ward 41(32.54) 2(7.41) 43(28.1) 37(22.42) 6(19.35) 43(21.94) 40(31.25) 4(14.29) 44(28.21)

Back ward 85(67.46) 25(92.59) 110(71.9) 76(46.06) 22(70.97) 98(50.00) 77(60.16) 19(67.86) 96(61.54)

Pointing forward 0 0 0 22(13.13) 1(3.23) 23(11.73) 2(1.56) 1(3.57) 3(1.92)

Ear

orie-

ntation

lateral 77(60.16) 20(58.82) 97(59.88) 156(77.61) 38(84.44) 194(78.86) 22(15.83) 7(12.96) 29(15.03)

Forward Erected 1(0.78) 6(17.67) 7(4.32) 16(7.96) 3(6.67) 19(7.72) 117(84.17) 47(87.04) 164(84.97)

Hanged down 50(39.06) 8(23.53) 58(35.8) 26(12.94) 4(8.89) 30(12.20) 0 0 0

Pendulous 0 0 3(1.49) - 3(1.22) 0 0 0

Back

profile

Straight 76(59.38) 21(61.76) 97(59.88) 171(85.07) 41(91.11) 212(86.18) 115(82.73) 42(77.78) 157(81.35)

Slops up towards

the rump 6(4.69) 0 6(4.69) 0 0 0 16(11.51) 3(5.56) 19(9.84)

Slops down from

the wither

26(20.31) 7(20.59) 33(20.37) 0 0 0 7(5.04) 4(7.41) 11(5.70)

Dipped 20(15.63) 6(17.65) 26(16.05) 30(14.93) 4(8.89) 34(13.82) 1(0.72) 5(9.26) 6(3.11)

Wattle Present 0 0 0 4(1.99) 0 4(1.63) 9(6.47) 0 9(4.66)

Absent 128(100) 34(100) 162(100) 197(98.01) 45(100) 242(98.37) 130(93.53) 54(100) 183(94.82)

Ruff Present 0 19(55.88) 19(11.73) 0 31(68.89) 31(12.60) 0 20(37.04) 20(10.36)

Absent 128(100) 15(44.12) 143(88.27) 201(100) 14(31.11) 215(87.40) 139(100) 34(62.96) 173(89.64)

Beard Present 32(25) 23(67.65) 55(33.95) 51(25.37) 41(91.11) 92(37.4) 25(17.99) 49(90.74) 74(38.34)

Absent 96(75) 11(32.35) 107(66.05) 150(74.63) 4(8.89) 154(62.60) 114(82.01) 114(82.01) 119(61.66)

72

Except 2% of Borena and 4.7% of Short-eared Somali does, wattle was totally absent in all

bucks of the three populations and Bati does. It was found that about 56, 69 and 37 % of Bati,

Borena and Short-eared Somali bucks had ruff, respectively. Over 90% of Borena and Short

eared Somali and 67.7% of Bati bucks had beard while about 25% of Bati and Borena as well

as 17.9% of Short-eared Somali does were bearded. This result indicated that the presence of

beard was more frequent in males. Similar results were also reported by Grum (2010) for the

same goat type and Dereje et al. (2013) in Hararghe highland goats. According to Hagan et

al., (2012), in addition to the thermoregulatory functions, the presence of wattle and beard

associated with reproduction traits such as higher prolificacy, higher milk yield, higher litter

size, fertility and conception rate.

In general, when appraised visually goats from the three areas were different (Figure 9),

which might be resulted due to breed and geographical differences. Thus, further to

understand the typical qualitative particularities of each goat population and transform into a

graphical display, multiple correspondence analysis was carried out on the recorded

qualitative traits. The bi-dimensional graph represented the associations among the different

categories of qualitative traits (Figure 8). The interpretation is based on points found in

approximately the same direction from the origin and in approximately the same region of the

space. As shown in the bi-dimensional plot below, the first and second identified dimensions

explained 8.9 and 7.1% of the total variation, respectively. On the identified dimensions, the

Bati goats clustered together with light brown “Dalcha” and deep brown coat color type,

straight and slightly convex head, dipped and sloping back, lateral and hanged down ears,

straight backward horn. The Borena goats also associated with plain white coat color,

presence of ruff, pendulous ear, forward pointing and rudimentary horn while the short-eared

Somali goats was associated together by forward erected ear, straight back, laterally oriented,

curved and spiral horn, spotted pattern, grey coat color and presence of wattle.

73

Figure 8. Association among qualitative traits categories via correspondence analysis

Legend:

Variable Name Levels and description

Coat color pattern CCP1=Plain CCP2=Patchy/pied CCP3=Spotted

Coat color type CC1= White CC2= Brown CC3=Black CC4= Grey CC5= Light red

CC6= White with brown CC7= White with Black CC8=White with light red

Facial/head profile FP1= Strait FP2= Slightly concave FP3= Slightly convex

Horn presence H1=Present H2=Absent H3= Rudimentary

Horn shape HS1=Straight HS2=Curved HS3=Spiral

Horn orientation HO1=Lateral HO2= Upward HO3= Back ward HO4= Pointing forward

Ear orientation EO1=Erected forward EO2=Pendulous EO3 =Hanged down EO4=Lateral

Back profile BP1=Straight BP2= Slops up towards the rump BP3= Slops down from the wither

BP4=Dipped

Wattle W1= Present W2= Absent

Ruff R1= Present R2= Absent

Bear B1= Present B2= Absent

74

Bati doe (left) and buck (right)

Borena doe (left) and buck (right)

Short-eared Somali does (left) and buck (right)

Figure 9. Physical appearances of indigenous Ethiopian adult goat populations

75

4.2.2. Quantitative characteristics

Quantitative characteristics are those that can be measured in some units. Knowledge of these

quantitative characteristics is important to implement genetic improvement (selection),

appreciate variations among goat populations so as to facilitate their sustainable use and

estimate live body weight from simple and more easily measurable variable as well as market

value in terms of cost of the animals. Therefore, general linear model procedure of SAS was

employed separately for female and male sample populations in order to assess variations of

continuous variables within and among populations. Least square means (± SE), coefficient of

variation and magnitude of population effect of body weight, body condition score and other

linear body measurements for does and bucks by population are presented in Tables 27 and

28, respectively.

4.2.2.1. Quantitative variation for does

Population-wise comparisons of least squares means of traits between populations revealed

that Bati does were significantly (p<0.05) heavier by weighing an average of 33.97±0.49 kg

and measuring widest chest (17.10±0.16cm) among the three different populations. As

compared with Borena does, they varied significantly (p<0.05) in only three traits (body

weight, chest width and horn length) of the nine measured traits and body condition score,

otherwise they were comparable in most of their body dimensions (body condition score,

body length, height at wither, chest girth, rump length, pelvic width and ear length).Therefore,

the result implied that, differences between the Bati and Borena does were little even though

most traits showed slightly higher average values in the Bati does except for height at wither

and chest girth which were a little higher for Borena does.

The Short-eared Somali does remained significantly (p<0.05) smallest in body weight, body

condition score and other leaner body measurements except horn length (Table 27). As

compared with the result found in the present study, slightly lower mean values of body

weight, body length, height at wither and chest girth for mature Bati does were reported by

Halima et al. (2012a) and Tesfaye et al. (2006). The variations could be due to different age

of animals included in the sample.

76

The respective overall R2 values ranged from 0.02 for body condition score to 0.56 for horn

length, indicated that about 56% of the variation in horn length was explained by the factor

included in the model (population) while only 2% for body condition score variability.

Table 27. Descriptive statistics of body weight (kg), body condition score and other body

measurements (cm) for does as affected by population types.

Traits

Population

Overall mean Bati

(N=128)

Borena

(N=201)

Short-eared

Somali (N=139)

LSM±SE CV

(%)

LSM±SE CV

(%)

LSM±SE CV

(%)

CV

(%)

R2

BC 2.65±0.08a 35.0 2.62±0.07a 38.0 2.32±0.07b 33.7 36.1 0.02

BW 33.97±0.49a 16.2 31.49±0.36b 16.4 24.67±0.28c 13.2 15.9 0.38

BL 62.97±0.27a 4.9 62.48±0.23a 5.3 57.85±0.41b 8.3 6.2 0.23

HW 68.74±0.29a 4.7 68.91±0.22a 4.5 62.88±0.25b 4.7 4.6 0.44

CG 73.55±0.36a 5.6 73.59±0.27a 5.1 67.27±0.28b 4.9 5.2 0.38

CW 17.10±0.16a 10.4 16.37±0.12b 10.6 15.35±0.14c 10.7 10.6 0.13

RL 15.25±0.08a 6.3 15.10±0.07a 6.3 14.07±0.08b 6.7 6.4 0.22

PW 14.36±0.09a 6.9 14.17±0.07a 6.9 13.73±0.13b 11.0 8.3 0.04

HL 13.87±0.24b 19.0 8.59±0.26c 40.8 17.51±0.34a 22.0 26.7 0.56

EL 15.65±0.12a 8.3 15.34±0.12a 10.7 12.99±0.10b 8.9 9.6 0.39

Means with different superscripts within the same row are statistically different (at least p<0.05); BC= Body

Condition, BL=Body Length, HW=Height at Wither, CG=Chest Girth, CW=Chest Width, RL=Rump Length,

PW=Pelvic Width, HL=Horn Length, EL=Ear Length; LSM =Least squares means, SE=standard errors,

CV=Coefficient of Variations and R2=magnitude of population effect

4.2.2.2. Quantitative variation for bucks

Though most traits showed higher average values in Bati bucks likewise in females,

differences with Borena bucks were not significant (p>0.05) for most of body characteristics

except pelvic width and horn length which were significantly (p<0.05) lower for Borena

bucks. Most of the body measurements estimated for Short-eared Somali bucks were

significantly (p<0.05) lower as compared with their counterparts in Bati and Borena. Despite

the other measurements the average values of pelvic width and horn length between Bati and

77

Short-eared Somali; and body condition score in the three populations were nearly similar

(Table 28). However, body condition score for Short-eared Somali bucks were slightly higher.

Such variation in terms of body condition score might be due to relatively small and compact

nature of the animals since the ratio of goat owners who provided special management for

bucks was limited (6.25%) in the area as reported under section 4.1.11.3 of this study.

The overall trait based coefficient of variation of bucks ranged 6.4 to 28.1% for height at

wither and horn length, respectively. The population effect (R2) values ranged from 0.01 for

body condition score to 0.57 for horn length. Traits with low overall R2 with the

corresponding high coefficient of variation (CV) values such as body condition score in the

present study reflected that the heterogeneity was within the population while the reverse

(high overall R2 and low CV values such as height at wither) indicated heterogeneity between

populations. Therefore, the varying coefficients of variation in this study attributed to both

population and individual differences.

78

Table 28. Descriptive statistics of body weight (kg), body condition score and other body

measurements (cm) for bucks as affected by population type.

Traits

Population

Overall mean Bati

(N=34)

Borena

(N=45)

Short eared Somali

(N=54)

LSM±SE CV LSM±SE CV LSM±SE CV CV R2

BC 3.06±0.16a 30.1 3.02±0.11a 23.9 3.22±0.10a 23.1 25.2 0.01

BW 41.30±0.85a 11.9 40.04±1.21a 20.3 30.62±0.67b 16.1 17.0 0.39

BL 65.59±0.59a 5.2 65.13±0.63a 6.5 57.28±0.69b 8.9 7.1 0.45

HW 76.09±0.68a 5.2 74.84±0.66a 6.0 64.98±0.67b 7.6 6.4 0.57

CG 81.25±0.95a 6.8 79.49±0.78a 6.6 71.24±0.73b 7.6 7.0 0.42

CW 18.12±0.29a 9.5 18.49±0.41a 15.0 16.37±0.30b 13.4 13.1 0.15

RL 16.41±0.21a 7.5 16.22±0.16a 6.8 15.44±0.23b 11.1 8.9 0.09

PW 15.94±0.27a 9.9 14.73±0.20b 9.1 15.91±0.30a 13.6 11.4 0.09

HL 18.57±0.73a 21.3 13.05±0.75b 32.2 19.92±1.10a 30.2 28.1 0.29

EL 14.50±0.43a 17.3 14.31±0.27a 12.9 12.01±0.32b 19.6 16.7 0.22

SC 27.07±0.36a 7.8 27.02±0.30a 7.5 25.81±0.37b 10.6 8.9 0.06

BC= Body Condition, BL=Body Length, HW=Height at Wither, CG=Chest Girth, CW=Chest Width, RL=Rump

Length, PW=Pelvic Width, HL=Horn Length, EL=Ear Length, SC=Scrotum Circumference; LSM =Least

squares means, SE=standard errors, CV=Coefficient of Variations and R2=magnitude of population effect

Means with different superscripts within the same row are statistically different (at least p<0.05).

4.2.3. Relationships between body weight and other body measurements

Coefficients of correlation between body weight and studied traits in this study varied from

strong (0.85) to low (0.18) and highly significant (p<0.01) to non-significant (Table 29). Most

measurements (BC, BL, HW, CG, CW, RL PW and HL) depicted positive and highly

significant (p<0.01) correlation with live body weight. Therefore, selection of one or more of

these traits except horn length (biologically which is not acceptable), may increase in live

body weight of these goat populations.

Correlation coefficient was consistently the highest between live body weight and chest girth

in both sexes for the populations. However, for Short-eared Somali bucks equally the highest

correlation coefficient was found for chest girth and height at wither with body weight. Even

79

though the correlation of body weight with chest girth was positive and significant for both

sexes, higher values were observed to be in bucks as compared with does within the same

population.

Due to positive and highly significant correlation between body weight and other linear body

measurements, traits in combination or individually could be measured to predict live body

weight. Particularly, chest girth would provide a good estimate for predicting live body

weight. Similarly, Halima et al. (2012a) and Grum (2010) for some Ethiopian goats; and

Tesfaye (2008) for sheep reported the highest correlation between body weight and chest

girth. This shows that chest girth might be the best trait to indicate live body weight for both

goats and other livestock species.

80

Table 29. Pearson’s correlation coefficients of quantitative traits for bucks (above diagonal) and does (below diagonal) Population Traits BW BC BL HW CG CW RL PW HL EL SC

Bati BW 0.57** 0.61** 0.58** 0.85** 0.47** 0.55** 0.47** 0.40* -0.18NS 0.55**

BC 0.52** 0.59** 0.27NS 0.54** 0.44** 0.14NS 0.27NS 0.21NS 0.14NS 0.34NS

BL 0.62** 0.35** 0.46** 0.77** 0.47** 0.41* 0.40* 0.28NS 0.04NS 0.40*

HW 0.40** 0.17* 0.48** 0.54** 0.01NS 0.44** 0.66** -0.06NS -0.31NS 0.54**

CG 0.82** 0.34** 0.57** 0.51** 0.50** 0.71** 0.62** 0.42* -0.17NS 0.56**

CW 0.68** 0.30** 0.46** 0.33** 0.61** 0.40* 0.34* 0.45* 0.07NS 0.31NS

RL 0.62** 0.29** 0.43** 0.41** 0.59** 0.59** 0.57* 0.34NS -0.24NS 0.60**

PW 0.53** 0.32** 0.39** 0.32** 0.49** 0.52** 0.51** -0.14NS -0.16NS 0.60**

HL 0.32** 0.07* 0.36** 0.18* 0.26** 0.18* 0.12* 0.15NS 0.08NS 0.26NS

EL 0.18* 0.04NS 0.20* 0.21* 0.23* 0.12NS 0.10NS 0.06NS 0.09NS -0.09NS

Borena BW 0.36* 0.80** 0.79** 0.86** 0.55** 0.76** 0.78** 0.69** -0.19NS 0.53**

BC 0.40** 0.27NS 0.51** 0.30* 0.10NS 0.11NS 0.22NS 0.52** -0.06NS 0.10NS

BL 0.67** 0.27** 0.77** 0.76** 0.28NS 0.66** 0.71** 0.60** -0.15NS 0.37*

HW 0.50** 0.08NS 0.50** 0.80** 0.43** 0.66** 0.75** 0.68** -0.36* 0.35*

CG 0.82** 0.25** 0.56** 0.54** 0.40** 0.74** 0.75** 0.84** -0.22NS 0.63**

CW 0.71** 0.31** 0.56** 0.50** 0.67** 0.52** 0.53** 0.25NS -0.43** 0.24NS

RL 0.57** 0.19** 0.58** 0.58** 0.60** 0.62** 0.76** 0.59** -0.32* 0.50**

PW 0.54** 0.19** 0.53** 0.43** 0.58** 0.50** 0.54** 0.53** -0.29NS 0.49**

HL 0.33* 0.11NS 0.24** 0.29** 0.38** 0.30** 0.27** 0.21** -0.12NS 0.51**

EL -0.13NS -0.13NS 0.31** 0.23** 0.23** 0.29** 0.23** 0.23** 0.15* -0.26NS

Short-eared

Somali

BW 0.69** 0.46** 0.79** 0.79** 0.53** 0.55** 0.26NS 0.69** 0.15NS 0.56**

BC 0.62** 0.49** 0.44** 0.56** 0.49** 0.28* 0.25NS 0.66** 0.01NS 0.43**

BL 0.25** 0.31** 0.51** 0.50** 0.25NS 0.24NS 0.20NS 0.38* -0.04NS 0.38**

HW 0.37** 0.13NS 0.17* 0.68** 0.40** 0.40** 0.24NS 0.64** 0.26NS 0.46**

CG 0.73** 0.44** 0.25** 0.32** 0.61** 0.59** 0.43** 0.65** 0.10NS 0.66**

CW 0.40** 0.16NS 0.07NS 0.01NS 0.53** 0.50** 0.12NS 0.46* 0.22NS 0.37**

RL 0.34** 0.19* 0.11NS 0.30** 0.45** 0.33** 0.42** 0.48** -0.04NS 0.52**

PW 0.24** 0.24** 0.03NS 0.12NS 0.40** 0.18* 0.26** 0.27NS -0.23NS 0.44**

HL 0.14NS 0.14NS 0.09NS 0.19* 0.37** 0.08NS 0.16NS 0.09NS 0.02NS 0.58**

EL 0.12NS 0.05NS -0.06NS 0.18* 0.02NS 0.12NS 0.17* 0.02NS 0.01NS -0.04NS BC= Body Condition, BL=Body Length, HW=Height at Wither, CG=Chest Girth, CW=Chest Width, RL=Rump Length, PW=Pelvic Width, HL=Horn Length, EL=Ear

Length, SC=Scrotum Circumference; NS= Non Significant; *p < 0.05, ** p< 0.01

81

4.2.4. Estimation of body weight of goats from other body measurements

The knowledge of live weight of animals is so important in the livestock production and

marketing practices (Birteeb and Ozoje, 2011). Even though the use of conventional weighing

scales is the best way of determining live weight of an animal, proper weight measurements

are often difficult in villages due to lack of weighing scales. To predict the live weight of

animals without weighing scales, mathematical equations can be developed based on actual

weight-linear body measurement data (Solomon and Kassahun, 2008).

The regression analysis of live body weight on different body measurements for does and

bucks are presented in Tables 30 and 31, respectively. The results of the stepwise multiple

regression analysis revealed that chest girth was the single variable of utmost importance in

the prediction of live body weight in the three populations in both sexes, with the exception of

Short-eared Somali bucks, where chest girth was not significant in the model. This result was

supported by highly correlation coefficient found between live body weight and chest girth

(Table 29). Even though the magnitude of improvement varied in both sex and population, the

inclusion of other linear body measurements with chest girth as well as with body condition

improved the accuracy of the prediction model (R2) in all cases. In agreement with the present

finding, several small ruminant researches (Tesfaye, 2008; Grum, 2010; Birteeb and Ozoje,

2011; Halima et al., 2012a) have reported comparatively high coefficient of determination

(R2) in body weight prediction equations taking chest girth as independent variable. In

addition chest girth was described to be practical comparing to other measurements like

wither height and body length.

The proportion of variance explained by body condition (R2 = 0.48) which accounted the

larger variation in body weight than other variables in Short-eared Somali bucks were smaller

than the variation explained by chest girth (R2≥ 0.60) in all does as well as in Bati and Borena

bucks. Nsoso et al. (2003) stated inconsistencies between the relationship of body condition

score and live body weight under extensive management system in dry and wet seasons.

Therefore, body condition score appeared to be a more useful trait in assessing nutritional

consequences than live weight body condition prediction under extensive management

systems.

82

When chest girth was the first variable explaining more variation, body weight was predicted

with better accuracy (R2) for bucks than does of all populations. The R2 value was higher for

Borena bucks than their counterparts in Bati while higher R2 values were equally recorded for

Bati and Borena does than Short-eared Somali counterparts. As a criterion, the value of R2

always increased as more independent variables added to the regression model. Therefore, R2

was not suitable for comparing the equations in a population which included different

independent variables. In the present study, inclusion of some independent variables in the

model does not produce R2 value improvement. However, in most cases smaller error mean

squares (MSE) were produced indicating better goodness fit of the models.

Even though the extra gain was small for some traits, the coefficient of determination (R2)

improvement obtained by combination of more than one estimates of body measurements

clearly indicated that weight can be estimated more accurately by combination of two or more

factors than only one. Nevertheless, according to Grum (2010) and Tesfaye (2008),

considering more variables under extensive management conditions will be unpractical due to

cost and accuracy problems. So, live body weight estimation using chest girth alone would be

better under extensive management conditions.

83

Table 30. Regression of live body weight on different body measurements for does

BC= Body Condition, BL=Body Length, HW=Height at Wither, CG=Chest Girth, CW=Chest Width, PW=Pelvic Width, HL=Horn Length, Ear Length,

SES=Short-Eared Somali

Population

Equation

Intercept Regression coefficients

α β1 β2 β3 β4 β5 β6 β7 R2 R2

Change

MSE

Bati

CG -47.34 1.11 0.67 0.00 3.16

CG+BC -46.10 1.03 1.65 0.78 0.11 2.63

CG+BC +CW -40.92 0.78 1.49 0.78 0.78 0.00 2.61

CG+BC +CW+BL -48.66 0.71 1.36 0.71 0.23 0.79 0.01 2.55

CG+BC+CW+BL+HL -47.43 0.71 1.46 0.67 0.18 0.16 0.79 0.00 2.53

CG+BC+CW+BL+HL+RL -49.60 0.68 1.43 0.59 0.17 0.16 0.45 0.80 0.01 2.52

CG+BC+CW+BL+HL+RL+HW -46.57 0.71 1.39 0.58 0.21 0.16 0.52 -0.10 0.80 0.00 2.51

SES

CG -26.45 0.76 0.61 0.00 2.00

CG+BC -20.02 0.62 1.23 0.68 0.08 1.83

CG+BC+HW -24.42 0.51 1.53 0.18 0.68 0.00 1.90

CG+BC+HW+EL -27.20 0.58 1.23 0.12 0.17 0.70 0.02 1.88

Borena

CG -51.48 1.13 0.67 0.00 2.97

CG+BL -63.68 0.90 0.47 0.73 0.06 2.68

CG+BL+BC -60.36 0.86 0.42 0.89 0.76 0.03 2.55

CG+BL+BC+CW -55.27 0.73 0.35 0.77 0.55 0.78 0.02 2.47

84

Table 31. Regression of live body weight on different body measurements for bucks

BC= Body Condition, BL=Body Length, HW=Height at Wither, CG=Chest Girth, CW=Chest Width, PW=Pelvic Width, HL=Horn Length, Ear Length,

SC=Scrotum Circumference; SES=Short-Eared Somali

Populatio

n

Equation Intercept Regression coefficients

α β1 β2 β3 β4 β5 β6 β7 β8 R2 R2

Change MSE

Bati

CG -19.20 0.75 0.72 0.00 2.67

CG+HW -30.25 0.67 0.23 0.74 0.02 2.58

CG+HW+PW -35.41 0.75 0.37 -0.78 0.77 0.03 2.47

CG+HW+PW+CW -44.99 0.63 0.52 -1.01 0.64 0.80 0.03 2.34

CG+HW+PW+CW+BL -38.97 0.80 0.62 -1.28 0.83 -0.42 0.82 0.02 2.20

SES

BC 15.84 4.59 0.48 0.00 3.40

BC+HW -3.60 3.56 0.35 0.58 0.10 3.27

BC+HW+CW -6.12 3.09 0.31 0.41 0.60 0.02 3.21

BC+HW+CW+BL -7.16 3.00 0.29 0.42 0.04 0.60 0.00 3.24

Borena

CG -66.68 1.34 0.74 0.00 4.24

CG+RL -74.42 1.02 2.07 0.77 0.03 3.99

CG+RL+HW -82.85 0.74 1.80 0.46 0.79 0.02 3.83

CG+BL+CW+HW -81.19 0.69 0.66 0.72 0.13 0.84 0.00 3.37

CG+BL+CW+ HW+SC -77.59 0.84 0.65 0.69 -0.02 -0.11 0.87 0.03 3.14

CG+BL+CW+ HW+SC+

EL

-93.35 0.73 0.60 0.82 0.14 0.08 0.56 0.88 0.01 3.04

CG+BL+CW+HW+SC+

EL+HL

-35.53 0.75 0.43 0.55 0.68 0.82 0.81 -0.49 0.95 0.07 2.18

CG+BL+CW+ HW+SC+

EL+HL+PW

-61.18 0.92 0.51 0.64 0.91 1.06 1.03 -0.71 -1.19 0.96 0.01 2.07

85

4.2.5. Multivariate analysis

Multivariate discriminant analysis was conducted using quantitative traits for does and bucks

separately to determine assignment (%) of each individual animal; to distinguish significant

discriminative traits; to obtain distances between sample populations and to observe the

spatial distribution of sample populations ( Aziz and Al-Hur, 2012; FAO, 2012).

4.2.5.1. Stepwise discriminant analysis

Result of the stepwise discriminant analysis is presented in Table 32. The stepwise

discriminant analysis procedure identified seven (HL, BW, EL, CG, HW, CW and PW) most

significant discriminating traits between does while it was five (HW, HL PW, CG and EL) in

bucks. The relative importance of the identified morphometric traits in discriminating the

three populations of goats was assessed at 5% level of significance. As shown in Table 32, in

both sexes all the predictors added some predictive power to the discriminant function

between sample populations as all are significant with (p<0.01) associated for each variable

against Wilk’s Lambda. When the most discriminating traits of both does (HL, BW, EL, CG,

HW, CW and PW) and bucks (HW, HL PW, CG and EL) separating the three goat

populations were selected chronologically, Wilk’s Lambda dropped to 0.18 and 0.19 with a

significant difference between the three goat populations (F = 5.42; p <0.05) and (F = 3.86; p

<0.05), respectively indicating the proportion of total variability not explained by the

discriminator variables between populations. This means that most (82% for female and 81%

for male) of the variability in the discriminator variables was due to differences between

populations rather than variation within populations. Similar to Wilk’s Lambda value, the

partial R2 static dropped down as significant discriminating variables added chronologically,

describing the amount of variability in each variable accounted for by the population

differences.

As depicted by the respective partial R2 and F-values; HL was found to have the highest

discriminating power in does followed by BW, EL, CG, HW, CW and PW in descending

order. In the meantime, HW had the highest discriminating power in male followed by HL,

PW, CG and EL from the highest. This implies that bucks required slightly fewer trait

86

measurements to differentiate between the three goat populations than does which asked

measurement of seven traits.

Table 32. Quantitative characters selected by stepwise discriminant analysis

Sex Step Variable

entered

Partial R2 Wilk’s

Lambda

F for entry Pr > F

Does 1 Horn length 0.511 0.489 242.54 < .0001

2 Body weight 0.419 0.284 167.20 < .0001

3 Ear length 0.169 0.236 46.96 < .0001

4 Chest girth 0.119 0.208 31.15 < .0001

5 Height at wither 0.081 0.192 20.27 .0005

6 Chest width 0.033 0.185 7.83 .0047

7 Pelvic width 0.023 0.181 5.42 .0019

Bucks 1 Height at wither 0.567 0.433 85.14 < .0001

2 Horn length 0.316 0.296 29.86 < .0001

3 Pelvic width 0.219 0.231 17.90 < .0001

4 Chest girth 0.124 0.203 8.97 .0002

5 Ear length 0.059 0.191 3.86 .0235

4.2.5.2. Discriminant analysis

Checking for multivariate normality, the estimated significant (p<.0001) multivariate

skewness and kurtosis values indicated that multi-attributes do not have a joint multivariate

normal distribution for the populations. Thus, non-parametric discriminant analysis (K-

Nearest Neighbor method) was used in the discriminant function to determine the percentage

of classification of individual animal in to a population. The performance of a discriminant

function in the classification of new observations can be evaluated by estimating the

probabilities of misclassification or error rates. Among the three Nearest Neighbor

87

Discriminant Function Analyses (K-2, K-3 and K-4) classification results, K-2 Nearest-

Neighbor Discriminant Function Analysis gave the smallest classification error in both sexes.

The overall average error count estimate of does was 10% accrediting 23, 4 and 3% for Bati,

Borena and Short-eared Somali goats respectively, while the overall error count estimate for

bucks was 14 % assigning 26% for Bati, 13% for Borena and 6% for Short-eared Somali

(Table 33). This means 90% of does and 86% of bucks for all populations were correctly

classified in their source population. However, the classification rates (hit rate) varied both in

sex and population.

In females, most Borena does (96.02%) were classified into their source population followed

by Short-eared Somali does (94.24%). The lowest classification rate (hit rate) was 77.34% for

Bati does. A total of 22.66% Bati does were misclassified as Borena (17.19%), Short-eared

Somali does (3.91%) and out of the three populations (1.56%) while 3.48% of Borena and

2.88% of Short-eared Somali does were wrongly assigned as Bati does but nearly none of

Borena does classified as Short-eared Somali does and vice versa. In males, most Short-eared

Somali bucks (94.4%) were classified into their source population followed by Borena

(86.7%). 11.1% of Borena bucks were wrongly assigned as Bati (8.9%) and Short eared

Somali (2.2%). On the other way, 26.5% of Bati bucks were misclassified as Borena. Very

few Short-eared Somali bucks (5.6%) were also wrongly classified as Bati and Borena. K-2

Nearest-Neighbor Discriminant Function Analysis method omitted 1.56% Bati does, 2.16%

Short-eared Somali does and 2.2% Borena bucks from their source population.

The proportion of individuals correctly reallocated is taken as measurement of the integrity of

that population, whereas the number of misclassified individuals (particularly between Bati

and Borena goats) suggested that the close/overlapping of measurements between populations

since the probability of intermingling between the studied populations is very low due to high

geographical distance between their habitats. The reason of relatively lowest classification

rate (hit rate) of Bati goats indicates the heterogeneity of the population which might be due

to intermixing of the breed with Afar goats as reported by respondents and observed during

the course of survey. On the other hand, the lowest misclassification error of Short-eared

88

Somali and Borena populations could be an indication of more uniformity within the

populations.

Table 33. Number of observation and percent of classification in parenthesis for sample

population by sex using K-Nearest Neighbour method

Sex From population Bati Borena Short-eared

Somali

Omitted Total

Does Bati 99(77.34) 22(17.19) 5(3.91) 2(1.56) 128(100)

Borena 7(3.48) 193(96.02) 1(0.5) 0(0.0) 201(100)

Short-eared Somali 4(2.88) 1(0.72) 131(94.24) 3(2.16) 139(100)

Total 110(23.5) 216(46.15) 137(29.27) 5(1.07) 468(100)

Error rate 0.23 0.04 0.06 - 0.10

Bucks Bati 25(73.5) 9(26.5) 0(0.0) 0(0.0) 34(100)

Borena 4(8.9) 39(86.7) 1(2.2) 1(2.2) 45(100)

Short-eared Somali 2(3.7) 1(1.9) 51(94.4) 0(0.0) 54(100)

Total 31(23.31) 49(36.8) 52(39.1) 1(0.8) 133(100)

Error rate 0.26 0.13 0.06 - 0.14

4.2.5.3. Canonical discriminant analysis

The canonical discriminant analysis was carried out to obtain Mahalanobis distances between

sample populations and to observe the spatial distribution of sample populations on canonical

variables by means of graph. It was conducted based on the most important discriminant

variables for does (HL, BW, EL, CG, HW, CW and PW) and bucks (HW, HL PW, CG and

EL) selected using step-wise discriminant analysis procedure. The Mahalanobis distances

between the three goat populations of both sexes according to the discriminating variables are

presented in Table 34. All pair wise distances of both sexes were significant (p<0.0001).

However, the higher squared Mahalanobis distance was found between bucks than does. The

largest distance (16.18 for bucks and 15.77 for does) was found between Borena and Short-

eared Somali goats while the closest distance (3.08 for does and 1.62 for bucks) was recorded

between Bati and Borena goats.

89

Table 34. Squared Mahalanobis distances between sampled populations based on pooled

covariance

Does

Bucks

Bati Borena Short-eared

Somali

Bati ** 3.08 8.60

Borena 1.62 ** 15.77

Short-eared

Somali

11.50 16.18 **

The canonical analysis allowed extracting three canonical variats (CAN1, CAN2 and CAN3)

for both bucks and does. However, the first two canonical variats (CAN1 and CAN2)

altogether explained about 100% and 99.96% of the total variation for does and bucks,

respectively with the remaining one variat in males accounting only 0.04% of the total

variation. Therefore, the last canonical variats was dropped as it is not significant in

separating sample populations in both sexes.

Spatial distributions of the three populations for each sex are presented in Figure 10. In both

sexes, CAN1 discriminated Borena from Short-eared Somali goat populations effectively,

keeping Borena and Bati populations closer on the right side of the X-axis. Though Bati goats

put closer to Borena goats, they positioned more or less between Borena and Short-eared

Somali goats. CAN2 is not effective in separating the three populations of both sexes except

biasing Bati goats to the right side of X-axis.

The similarities between Bati and Borena goats and significance divergence of Short-eared

Somali population from the two populations might suggest possible genetic similarities and

differences. Even though, the two populations (Bati and Borena) are very similar in

quantitative traits measurements, but even they could be genetically quite distant. Hence,

further molecular marker information for comparative genetic analysis needed to validate

information from morphological characterization.

90

Figure 10. Spatial distributions of does (left) and bucks (right) on the first two canonical variats (CAN1 and CAN2)

91

4.3. On-farm Goat growth Performance Evaluation and Monitoring

4.3.1. Growth performance

Knowing the growth dynamics of young animals may be used as one of the indicators to

evaluate the level of adaptation under conditions of a production system which is different

from its origin place (Kume and Hajno, 2010). To see the effect of non-genetic factors

(population and/or production environment, sex of kid, parity of dam and type of birth) on the

growth performance of kids, weights at different ages (birth, 30, 90 and 180 days) for Bati,

Borena and Short-eared Somali goats were recorded.

4.3.2. Average body weight at different ages (birth, 30, 90 and 180 days)

Descriptive statistics (LSM±SE) of body weights (kg) from birth to 180 days of age for

studied three goat types are presented in Table 35. Bati goats had the heaviest overall live

weight at birth (2.70±0.05kg) followed by Borena (2.42±0.05kg) which were significantly

(p<0.0001) higher than that of Short-eared Somali goats (2.19±0.08kg). The birth weight of

Bati goats observed in this study was close to the result of Tesfaye et al. (2006) for the same

goat type but higher than the values reported by Belay (2008) for Abergele and Central

highland goats in Ethiopia. Zeleke (2007) also reported higher value of birth weight (3.19kg)

for Somali goats in extensive management system at Alemaya (currently Haramaya)

university as compared with the result found in the present study for Short-eared Somali

goats. The birth weight of Borena goats found in this study was comparable with the birth

weight of Arsi-Bale and Abergelle goats in intensive management system reported by Mahlet

(2008) and Birhane and Eirk (2006), respectively.

Despite their significant (p<0.05) difference in average birth weight, the Bati and Borena

goat kids had nearly equal overall average live weight at 90 days of age. However, the overall

growth rate of Borena goat kids showed retarding trend after 90 days of age while Bati goat

kids maintained their superiority thereafter (Figure 11).

Kume and Hajno (2010) stated that the growth period of young animals until the puberty age

can be divided into three phases: (i) maternal phase; from birth to weaning, (ii) phase of

92

development of bio-physiological mechanisms; from weaning to 6 months old and (iii)

growth phase; from the age of 6 months to puberty. According to these authors, the second

phase tells us more information in relation to the adaptation rate and/or response of breed

under the production environment. Therefore, the reason for retarded growth rate seen in

Borena kids after 90 days of age might be due to the environmental stress (feed shortage)

during short dry season (June-August) and long dry season “Boona” (December-February) on

the second phase of development.

The results in this study indicated that male kids weighed more than doe kids at birth and

were heavier up to 90 days for all studied goat types (Table 35). The result was in consonance

with the findings of other authors who observed that male kids were superior to their female

counterparts (Banerjee and Jana, 2010; Mabrouk et al., 2010; Belay and Mengistie, 2013) but

contradicted with the report of Khanal et al. (2005) and Bharathidhasan et.al, (2009) who

reported that the weight of the female kids were higher than their male counterparts.

According to Nkungu et al. (1995), the heavier body weight obtained for males may be

attributed to the effect of the male sex hormone (androgen) which is responsible for the

development of male characteristics.

Kids born as single were significantly heavier (p<0.05) than twins, up to180 days of age in

Bati kids and 30 days in Borena kids (Table 35). The heavier body weight of single born kids

attributed to the weight advantage to competition for nutrients (milk) and the less inter-uterine

space in cases where does carry two or more fetuses as compared to one (Wilson,1989 cited in

Zahraddeen et al., 2008). This study also observed that Short-eared Somali kids born single

were non-significantly heavier than their twin counterparts. Zahraddeen et al., (2008)

reported similar findings for local Nigerian goats.

As shown in Table 35, birth weight of kids was significantly affected by parity of doe in all

studied goat types. Bati and Borena, kids from the first parity had relatively lower birth

weights than kids in other parity.

93

Table 35. Descriptive statistics (LSM±SE) of body weights (kg) from birth to 180 days of age

for Bati, Borena and Short-eared Somali goats

Pop. Factors BW 30 DW 90 DW 180DW

N LSM±SE N LSM±SE N LSM±SE N LSM±SE

Overall 308 *** 292 *** 270 *** 248 ***

Bati 139 2.70±0.05a 133 6.14±0.10a 119 10.44±0.18a 110 15.57±0.19a

Borena 123 2.42±0.05b 114 5.51±0.10b 108 10.48±0.12a 101 13.41±0.20b

SES 46 2.19±0.08c 45 4.67±0.16c 43 8.76±0.30b 37 13.10±0.32b

Bati Sex * * ** NS

Female 60 2.58±0.07b 57 5.81±0.15b 50 9.56±0.32b 46 15.9±0.38

Male 79 2.81±0.07a 76 6.26±0.14a 69 10.58±0.29a 64 16.15±0.34

Parity ** * * NS

1 26 2.43±0.11c 26 5.8±0.22ab 22 9.46±0.48b 19 16.0±0.58

2 26 2.62±0.11bc 25 5.55±0.22b 23 9.81±0.47b 23 15.64±0.55

3 31 2.74±0.1ab 29 6.15±0.20a 28 10.5±0.42ab 26 15.86±0.5

4 26 3.0±0.11a 23 6.31±0.24a 21 9.48±0.5b 19 16.0±0.61

≥5 30 2.69±0.1bc 30 6.38±0.20a 25 11.06±0.44a 23 16.6±0.51

TB * * * *

Single 47 2.82±0.08a 46 6.28±0.17a 43 10.57±0.36a 40 16.66±0.42a

Twin 92 2.57±0.06b 87 5.79±0.13b 76 9.57±0.29b 70 15.38±0.33b

Borena Sex ** ** * NS

Female 64 2.21±0.09b 59 5.14±0.17b 55 10.28±0.34b 52 14.35±0.31

Male 59 2.59±0.11a 55 5.77±0.17a 53 11.01±0.28a 49 14.20±0.29

Parity ** NS NS NS

1 13 1.87±0.17b 13 5.02±0.31 13 10.68±0.51 13 14.7±0.52

2 31 2.54±0.1a 26 5.39±0.2 26 10.89±0.33 23 14.35±0.35

3 31 2.44±0.11a 31 5.54±0.21 28 9.86±0.35 28 13.80±0.35

4 19 2.67±0.15a 15 5.5±0.30 14 11.22±0.5 13 14.55±0.53

≥5 29 2.47±0.12a 29 5.84±0.23 27 10.57±0.38 24 13.97±0.42

TB * * NS NS

Single 87 2.53±0.07a 80 5.71±0.14a 76 10.67±0.35 72 14.43±0.24

Twin 36 2.27±0.11b 34 5.2±0.21b 32 10.62±0.23 29 14.12±0.37

SES Sex ** ** * NS

Female 19 1.7±0.17b 19 3.61±0.53b 17 8.71±.0.7b 14 11.73±0.88

Male 27 2.27±0.16a 26 4.74±0.58a 26 9.84±0.63a 23 13.43±0.86

Parity * NS NS NS

1 11 1.96±0.17b 11 4.14±0.68 11 10.38±0.78 8 11.81±1.09

2 9 1.78±0.2b 9 4.77±0.65 9 9.53±0.82 5 12.44±1.16

3 17 1.63±0.19b 17 3.60±0.57 15 8.41±0.78 16 13.17±1.04

4 3 2.52±0.24a 3 4.30±0.70 2 7.38±1.11 3 13.01±1.31

≥5 6 2.04±0.2ab 5 4.08±0.79 6 10.29±0.81 5 12.45±1.13

TB NS NS NS NS

Single 35 2.03±0.14 24 3.92±0.45 32 8.86±0.55 26 12.99±0.73

Twin 11 1.94±0.2 11 3.85±0.56 11 9.54±0.82 11 12.16±1.05

LSM =least square means, SE= standard errors, N= number of observation, BW=Birth Weight, DW= Day Weight, TB=Type

of Birth, NS= Non Significant Pop. = population, SES = Short-eared Somali; Means in the same column with different

superscripts are significantly different; *, p<0.05, **, p<0.01, *** p<0.0001

94

The effect of parity was retained up to 90 days of age for Bati goats with inconsistent

increment of live weight in the advancement of parity at different ages. This result was in line

with the report of Deribe (2009) and in contrast with the report of Zahraddeen et al. (2008)

who reported inconsistent and consistent increment of live weight in the advancement of

parity at different ages, respectively. The effect of parity on live weight was non-significant

after birth in both Borena and Short-eared Somali kids.

Generally, similar to the results reported in elsewhere in Ethiopia (Zeleke, 2007; Deribe,

2009; Belay and Mengistie, 2013); West Bengal (Banerjee and Jana, 2010); Albania (Kume

and Hajno, 2010) and Tunisia (Mabrouk et al., 2010); non-genetic factors (goat type, sex of

kids, parity of dam and type of birth) significantly (p<0.05) influenced the weight of young

goats at different ages, except type of birth in Short-eared Somali kids.

Figure 11. Male, female and overall growth rate trends of three young Ethiopian goats (birth

to 180 days)

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

0 30 60 90 120 150 180 210Aver

age

live

wei

gh

t (k

g)

Age (days)

Bati overallBati malesBati femalesBorena overallBorena malesBorena femalesShort-eared Somali overallShort-eared Somali malesShort-eared Somali females

95

4.3.3. Average daily weight gain (birth - 90 days)

There was no significant difference in average daily weight gain from birth to 90 days between

Bati and Borena kids but Short-eared Somali kids had significantly (p<0.05) lighter average

daily weight gain at the maternal phase than the two goat types (Table 36). The average daily

weight gain found at this phase for Bati and Borena kids in the present study was higher than the

report of Deribe (2009) as well as Belay and Mengistie (2013) for indigenous goats in Southern

and Northern part of Ethiopia, respectively. The average daily weight gain (birth to 90 days)

obtained for Short-eared Somali kids in this study was lower than the previous reports of

Zeleke (2007) for Somali goats. According to the later author, such variations in pre-weaning

daily weight gain can be attributed to the management difference of both dams and kids at

early age.

Sex of kids affected significantly (p<0.05) the total daily weight gain (birth to 90 days) of

Bati goat kids thus males had the heaviest daily weight gain (86.82±3.05g/day) as compared

to their female counterparts (78.17±3.37g/day) while both Borena and Short-eared Somali

male goat kids had non-significant (p>0.05) heavier daily weight gain than their female

counterparts.

Like that of sex, parity was not-significantly (p>0.05) affected the average daily weight gain

(birth to 90 days) of both Borena and Short-eared Somali kids but it had a significant

(p<0.05) effect on Bati kids daily weight gain. In the literature, Deribe (2009) and Dadi et al.

(2008) respectively, reported non-significant and significant effect of parity on the pre

weaning daily weight gain of local goats in Ethiopia. As it was reported by different authors, kids

from 3rd and 4th parity had relatively higher daily weight gain as compared with kids from 1st

and ≥5th party (Dadi et al., 2008; Zahraddeen et al., 2008); Belay and Mengistie, 2013).

However, in this study, Bati goats kids from 5th parity were significantly (p<0.05) heavier than

kids from the 1st, 2nd, and 4th parities and none-significantly (p>0.05) kids from the 3rd parity

(Table 36). This result implied that, Bati does even ≥5th parity can be used as breeders in order

to obtain an efficient and maximum production.

96

4.3.4. Average daily weight gain (91-180 days)

The average daily weight gain (91-180 days) for Bati, Borena and Short-eared Somali goat

kids are summarized in Table 36. For all cases, daily weight gain after 90 days of age was

lighter as compared with before 90 days of age. This study observed significant (p<0.05)

difference in overall daily weight gain from 91 to 180 days of age between populations.

As expected and documented in literatures (Zeleke, 2007; Zahraddeen et al., 2008; Banerjee

and Jana, 2010; Mabrouk et al., 2010; Belay and Mengistie, 2013) males have heavier daily

weight gain before and after weaning. On the other hand, Bazzi and Tahmoorespur (2013)

reported heavier average pre-weaning daily gain of females than males. In this study, it was

found that non-significant (p<0.05) heavier daily weight gain in male kids before and after 90

days of age, except in Bati kids where sex exerted significant effect on daily weight gain in

favor of males (birth to 90 days). Similarly, non-significant effect of sex on daily weight gain

of kids from birth to 60 and 100 days of age were reported by Zahradeen (2008) and Nkungu

et al. (1995), respectively.

Significant (p<0.05) parity effect was also observed in this study with respect to kids daily

weight gain in each population from 91 to 180 days of age. Even though, the increment of

daily weight gain in the advancement of parity at different ages was inconsistent, in most

cases kids at 2nd, 3rd and 4th parity had better daily weight gain (Table 36).

Across all goat types, the influence of type of birth on daily weight gain of kids at different

ages (birth, 30, 90 and 180 days) was non-significant (p>0.05) only with numerical

differences (not statistically significant) in favor of kids born as single. Similarly, irrespective

of significantly higher birth and weaning weight of kids born as single, Bazzi and

Tahmoorespur (2013) found non-significant difference in average daily weight gain between

kids born as single and twin from 6 to 9 months of age. Whereas Busahra et al. (2013), Zeleke

(2007) and Madibela et al. (2002) reported higher pre weaning daily weight gain for single

kids compared with multiple births.

97

Table 36. Descriptive statistics (LSM±SE) of daily weight gain (birth-90 and 91-180 days) for Bati, Borena and Short-eared Somali

goats

Bati Borena Short-eared Somali

Factors ADWG g/day

(birth-90 days)

ADWG g/day

(91-180 days)

ADWG g/day

(birth -90 days)

ADWG g/day

(91-180 days)

ADWG g/day

(birth -90 days)

ADWG g/day

(91-180 days)

N LSM±SE N LSM±SE N LSM±SE N LSM±SE N LSM±SE N LSM±SE

Overall 119 86.22±2.02 108 56.49±1.70 108 89.88±2.02 101 32.96±1.76 43 73.15±3.20 34 47.20±3.08

Sex * NS NS NS NS NS

Female 50 78.17±3.37b 46 55.83±3.01 55 90.41±3.23 52 30.85±2.66 17 76.65±7.57 12 36.71±6.91

Male 69 86.82±3.05a 62 59.15±20.75 53 94.95±3.22 49 33.67±2.8 26 84.22±7.30 22 43.61±6.91

Parity * * NS * NS *

1 22 77.61 ±5.07bc 19 59.99±4.62abc 13 98.53±5.75 13 31.46±4.71ab 11 93.56±9.05 8 21.61±8.61b

2 23 80.61±4.96bc 23 60.76±4.35ab 26 92.87±5.70 23 36.63±3.22a 9 85.59±9.45 5 34.42±9.35b

3 28 87.08±4.4ab 26 51.87±3.93bc 28 83.26±3.93 28 38.02±3.20a 15 74.05±9.02 14 44.19±8.75ab

4 21 73.51±5.33c 17 65.44±5.02a 14 97.06±5.70 13 20.53±4.86b 2 57.31±12.89 2 68.9±11.9a

≥5 25 93.63±4.69a 23 49.40±4.20c 27 91.67±4.38 24 34.68±3.8b 6 91.69±9.35 5 31.77±9.0b

TB NS NS NS NS NS NS

Single 43 86.5±3.81 40 58.14±3.36 76 91.08 ±2.58 72 34.68±2.14 32 75.88±6.31 23 43.74±5.7

Twin 76 78.48±3.08 68 56.85±2.74 32 94.26±3.99 29 29.85±3.39 11 84.99±9.53 11 36.57±8.96

LSM =least square means, SE= standard errors, ADWG = Average daily weight gain, N= number of observation, TB=Type of Birth, NS= Non Significant

Pop. = population, SES = Short-Eared Somali; Means in the same column with different superscripts are significantly different; *, p<0.05

98

5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.1. Summary

Ethiopia has large number of (24.06 million heads) widely distributed multi-functional goat

populations. Understanding both the management systems and morphological characteristics

of these goat populations simultaneously addressing several constraints will help to craft

successful improvement and utilization strategies. Therefore, this study was designed to

characterize the production systems, morphological features and productive and reproductive

performances of Bati, Borena and Short-eared Somali goats under their home tract that can

help for designing community based goat improvement and utilization plan.

In number, goats were the predominant species in Bati, Borena and Siti areas. The mean goat

flock size (44.02±3.33) owned per household in Siti was significantly (p<0.05) higher

followed by Borena (23.08±1.94) and Bati (8.99±0.59). Breeding does made a major share

within a flock accounting 3.51±0.91, 9.30±0.78 and 13.30±0.84 in Bati, Borena and Siti areas,

respectively. In Borena and Bati areas income generation was the primary reason of goat

rearing while in Siti area milk production was a main reason of goat keeping. Traits like body

size, fast growth rate, milk yield, reproduction rate, drought tolerance and disease resistance

were preferred by the producers with some discrepancies in relation to the primary production

objectives across areas. Higher percentage of respondents in Siti (98.26%) and Borena

(94.70%), and below half of the respondents (28.57%) around Bati area reported goat milking

for household consumption.

Natural pasture (shrubs and bushes) was the primary feed source in all the study areas. Herded

free natural browsing was the commonest feeding practice in Borena and Siti areas while in

Bati area most of the time movement of goats was limited in small privet and/or communal

browsing land. Feed and water shortage, disease incidence and recurrent drought were the

major goat production challenges that have been hindering their production and productivity

across the study areas. The common goat diseases reported were pneumonia, pasteurellosis,

babesiosis, anthrax and goat pox, external parasites, contagious caprinepleuro pneumonia

99

(CCPP), coenurosis, diarrhea and pest des petit ruminants (PPR) with various degree of

economic importance across study areas.

The studied goat populations have a wide range of coat colors. Plain brown (dark and light)

(51.85%) was the predominant coat color observed on Bati goats of both sexes, while plain

white coat color was most frequently observed on Borena (71.54%) and only 36.27% on

Short-eared Somali goat populations. Though most quantitative traits showed slightly higher

average values in the Bati goats, differences with Borena goats were not significant (p>0.05)

whereas the Short-eared Somali goats remained significantly (p<0.05) the smallest for most of

the qualitative traits. The highest correlation coefficient was found between live body weight

and chest girth in does and bucks except in Short-eared Somali bucks where body condition

score explained higher variation (R2=48%). Hence, chest girth was the first variable

explaining more variation in body weight of Bati, Borena and Short-eared Somali does

(R2=67, 67 and 61 %, respectively) and Bati and Borena bucks (R2=72 and 74%,

respectively).

Nearest Neighbor Discriminant Function Analysis classified most of Borena does into their

source population followed by Short-eared Somali does. The stepwise discriminant analysis

procedure identified seven most significant discriminating traits between the three does

populations while it was five for bucks. From the identified variables horn length and height

at wither had the most discriminating power in does and bucks, respectively. The largest

Mahalanobis' distance was found between Borena and Short-eared Somali goats while the

least differentiation was observed between Bati and Borena goats.

In the present study, in most cases, the influence of non-genetic factors (sex, parity of dam

and type of birth) and genetic factor (goat ecotype) on the average live weight and daily

weight gain of young goats at different ages was significant (p<0.05). However, type of birth

had non-significant effect on daily weight gain of all goat types and live weight of Short-eared

Somali kids at different ages. Bati kids had the heaviest overall live weight at birth

(2.70±0.05kg) followed by Borena (2.42±0.05kg) which were significantly (p<0.0001) higher

than that of Short-eared Somali goats (2.19±0.08kg). Despite the significant (p<0.05) heavier

birth weight of Bati kids (overall), Borena kids had non-significant (p<0.05) heavier daily

100

weight gain (89.88±2.02 g/d) from birth to 90 days of age, which do not maintained

thereafter.

5.2. Conclusions and Recommendations

The higher proportion of male household heads in Bati (93.88%) Borena (68.18%) and Siti

(79.13%) area, respectively, may lead men to have disproportionate benefits from livestock sale.

The absence of secular education in most of goat keepers particularly in Borena and Siti areas

could have also negative impact for the adoption of technologies. As perceived by the

producers the goat populations in the studied areas have developed combinations of adaptable

characteristics which enable them to survive and reproduce in those harsh environments.

Based on the canonical discriminant analysis result Borena and Short-eared Somali goats

were distantly related in morphometric characteristics while the least differentiation was

between Bati and Borena goats. Since both Bati and Borena kids had relatively higher growth

rate at the maternal phase of development (birth-90 days) than Short-eared Somali kids, they

are more promising in terms of growth performance than Short-eared Somali goats. The

diversified functions of goats and constraints found in the present study across the study areas

speak loud the necessity to formulate holistic research-for-development strategies.

Since the reason of goat keeping, management practices and agro-ecology varied across the

study areas, the recommendations presented below need to be revised within the respective

local contexts and implemented taking into account producers’ interests. Implementation of

the recommendations in the absence of producers’ participation in the initial phase is unlikely

to be successful and leads a total failure. This is, therefore, to suggest the following issues for

action by research and /or development institutes:

Farmers/pastoralists should be encouraged to discuss and take decision together with

researchers, development experts and decision makers.

Implementing community-based animal health management programs and

strengthening animal health centers for better animal health care will maximize the

productivity of goats in studied areas.

101

To overcome feed shortage in Borena and Siti, the productivity of rangelands should

be restored by bush clearing and promoting community regulations for the proper

utilization of the existing rangelands while in Bati area farmers should be encouraged

to grow forage trees in soil conservation structures and stock exclusion areas

To prevent pregnancy from uncontrolled natural mating and to increase productivity,

establishing buck selection and management systems at community level for open

mating systems and castrating non-productive bucks is an alternative.

For adequate water supply Borena and Siti, infrastructures should be developed and

strengthen that could help community-based water-point management practices.

The producers’ perception about their goats’ adaptability and morphometric trait

differences and similarities are suggested to be supported with further genetic analysis

studies and steps need to be taken to conserve these animal genetic resources under

their production environment.

Linear measurements could be valuable to estimate live body weight for those farm

communities where sensitive weighing scales are not readily available.

For better age at first kidding of Short eared Somali goats, management practices

needed to be improved

The Bati and Borena goats showed relatively better growth performance at the

maternal phase of development (birth-90 days), hence, improvement of these goat

types can be made through better husbandry practices including selection.

102

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115

7. APPENDICES

Appendix A: Different tables

Appendix Table 1. Ranking farming and non-farming activities by study area

Activities and

purpose

Bati area Borena Siti

Food supply Rank 1 Rank 2 Rank 3 Index Rank 1 Rank 2 Rank

3

Index Rank1 Rank 2 Rank3 Index

Livestock and livestock

product selling

3 90 1 0.375 65 66 1 0.509 104 11 0 0.797

Crop production 94 2 0 0.565 67 51 0 0.470 11 24 0 0.193

Hand craft 1 2 5 0.024 1 0 1 0.006 0 0 0 0

Trading 0 1 8 0.020 0 2 3 0.011 0 2 0 0.010

Daily laborer 0 1 6 0.016 0 0 3 0.005 0 0 0 0

Income generation 0

Livestock and livestock

product selling

69 22 6 0.549 125 7 0 0.706 115 0 0 0.932

Crop production 16 42 8 0.312 6 61 1 0.256 0 6 0 0.032

Hand craft 1 6 3 0.038 0 1 0 0.004 0 0 0 0

Trading 5 6 6 0.071 0 2 5 0.016 0 3 1 0.019

Daily laborer 5 1 3 0.043 1 2 3 0.018 0 3 0 0.016

116

Appendix Table 2. Percentages of households castrate their buck and method of castration used by study areas

Do you practice castration? Bati area (N=98) Borena (132) Siti (115)

N % N % N %

Yes 68 69.39 29 21.97 112 97.39

No 30 30.61 103 78.03 3 2.61

Castration method

Traditional only 39 57.38 25 89.29 97 86.61

By veterinarians only 18 26.47 3 10.71 2 1.79

Both 11 16.18 0 0 13 11.61

Appendix Table 3. Ranking of category of goats sold first in study areas

Category

Bati Area Borena Siti

Rank1 Rank2 Rank3 Index Rank1 Rank2 Rank3 Index Rank1 Rank2 Rank3 Index

Buck kids 28 23 16 0.236 77 16 25 0.360 30 30 35 0.271

Doe kids 5 21 26 0.135 1 46 19 0.142 0 2 20 0.035

Breeding

does

2 9 10 0.055 0 1 6 0.010 0 0 0 0

Breeding

bucks

1 7 6 0.037 5 2 1 0.025 0 0 1 0.001

Castrates 37 9 14 0.231 6 - 9 0.034 49 31 20 0.335

Old does 21 19 15 0.188 40 32 39 0.278 29 28 15 0.231

Old bucks 11 15 10 0.118 5 38 30 0.151 13 18 11 0.126

117

Appendix Table 4. Best models for Bati does regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.6668 0.6641 72.2377 292.0983 3.16213 297.77083 CG

1 0.4630 0.4586 191.0254 352.2257 4.01424 357.89824 CW

2 0.7437 0.7396 29.3775 261.0099 2.78429 269.51871 BC CG

2 0.7177 0.7131 44.5589 273.2057 2.92235 281.71452 CG CW

3 0.7777 0.7722 11.5960 245.1110 2.60400 256.45609 BC CG CW

3 0.7602 0.7543 21.7637 254.6279 2.70422 265.97303 BC BL CG

4 0.7881 0.7811 7.5280 241.0688 2.55279 255.25024 BC BL CG CW

4 0.7872 0.7802 8.0465 241.5966 2.55814 255.77801 BC CG CW HL

5 0.7933 0.7847 6.4743 239.9149 2.53152 256.93255 BC BL CG CW HL

5 0.7915 0.7829 7.5099 240.9933 2.54237 258.01100 BC BL CG CW RL

6 0.7968 0.7865 6.4510 239.7808 2.52069 259.63473 BC BL CG CW RL HL

6 0.7959 0.7856 6.9870 240.3496 2.52639 260.20360 BC BL HW CG CW HL

7 0.8004 0.7886 6.3498 239.5256 2.50880 262.21582 BC BL HW CG CW RL HL

7 0.7970 0.7850 8.3095 241.6302 2.52984 264.32044 BC BL CG CW RL PW HL

8 0.8008 0.7871 8.1303 241.2876 2.51712 266.81418 BC BL HW CG CW RL PW HL

8 0.8006 0.7869 8.2382 241.4047 2.51829 266.93119 BC BL HW CG CW RL HL EL

9 0.8010 0.7856 10.0000 243.1462 2.52653 271.50903 BC BL HW CG CW RL PW HL EL

Appendix Table 5. Best models for Bati bucks regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.6909 0.6795 11.4217 58.3047 2.64327 61.03933 CG

1 0.3743 0.3512 48.7353 78.7589 3.76097 81.49352 SC

2 0.7187 0.6971 10.1517 57.5767 2.56986 61.67854 BL CG

2 0.7110 0.6888 11.0604 58.3609 2.60485 62.46281 BC CG

3 0.7362 0.7045 10.0921 57.7166 2.53804 63.18578 BC HW CG

3 0.7360 0.7043 10.1130 57.7361 2.53889 63.20527 BL CG PW

4 0.7724 0.7345 7.8190 55.4292 2.40580 62.26563 BL HW CG PW

4 0.7614 0.7217 9.1170 56.7999 2.46333 63.63634 BC HW CG PW

5 0.8185 0.7791 4.3857 50.8640 2.19453 59.06774 BL HW CG CW PW

5 0.7935 0.7486 7.3369 54.6128 2.34106 62.81660 BC BL HW CG PW

6 0.8290 0.7823 5.1554 51.1457 2.17835 60.71674 BC BL HW CG CW PW

6 0.8285 0.7818 5.2085 51.2220 2.18122 60.79310 BL HW CG CW PW SC

7 0.8378 0.7838 6.1135 51.6065 2.17123 62.54486 BL HW CG CW PW HL SC

7 0.8353 0.7804 6.4077 52.0494 2.18787 62.98778 BL HW CG CW RL PW SC

8 0.8422 0.7791 7.5955 52.8097 2.19449 65.11536 BL HW CG CW RL PW HL SC

8 0.8405 0.7767 7.7995 53.1261 2.20649 65.43174 BC BL HW CG CW PW HL SC

9 0.8452 0.7718 9.2464 54.2600 2.23026 67.93296 BL HW CG CW RL PW HL EL SC

9 0.8442 0.7704 9.3613 54.4421 2.23727 68.11506 BC BL HW CG CW RL PW HL SC

10 0.8473 0.7624 11.0000 55.8658 2.27585 70.90601 BC BL HW CG CW RL PW HL EL SC

118

Appendix Table 6. Best models for Borena does regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.6584 0.6565 70.1818 408.6711 3.01957 415.10097 CG

1 0.4999 0.4971 186.2394 478.7934 3.65342 485.22323 CW

2 0.7177 0.7146 28.7252 375.5644 2.75239 385.20919 BL CG

2 0.7081 0.7049 35.7669 381.7276 2.79888 391.37240 CG CW

3 0.7433 0.7391 11.9529 360.0477 2.63173 372.90745 BL CG CW

3 0.7433 0.7390 12.0196 360.1130 2.63220 372.97279 BC BL CG

4 0.7815 0.7562 0.6671 348.5588 2.54409 364.63350 BC BL CG CW

4 0.7463 0.7406 11.8062 359.9341 2.62396 376.00882 BL CG CW EL

5 0.7622 0.7555 2.1741 350.0387 2.54762 369.32829 BC BL CG CW RL

5 0.7617 0.7550 2.4865 350.3684 2.54990 369.65803 BC BL CG CW EL

6 0.7623 0.7543 4.0561 351.9140 2.55394 374.41858 BC BL CG CW RL EL

6 0.7622 0.7542 4.1332 351.9955 2.55451 374.50004 BC BL CG CW RL HL

7 0.7624 0.7529 6.0058 353.8609 2.56082 379.58037 BC BL CG CW RL HL EL

7 0.7623 0.7529 6.0492 353.9067 2.56114 379.62623 BC BL CG CW RL PW EL

8 0.7624 0.7515 8.0009 355.8557 2.56809 384.79013 BC BL CG CW RL PW HL EL

8 0.7624 0.7515 8.0051 355.8601 2.56812 384.79450 BC BL HW CG CW RL HL EL

9 0.7624 0.7501 10.0000 357.8547 2.57545 390.00406 BC BL HW CG CW RL PW HL EL

Appendix Table 7. Best models for Borena bucks regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.8175 0.8110 56.1923 79.5698 3.64732 82.37219 CG

1 0.7337 0.7242 93.9401 90.9077 4.40596 93.71011 HW

2 0.8782 0.8691 30.8747 69.4495 3.03488 73.65312 BL CG

2 0.8680 0.8582 35.4600 71.8571 3.15913 76.06065 HW CG

3 0.9111 0.9008 18.0447 61.9978 2.64194 67.60260 BL CG CW

3 0.8934 0.8811 26.0162 67.4441 2.89297 73.04886 HW CG CW

4 0.9167 0.9034 17.5048 62.0320 2.60742 69.03801 BL HW CG CW

4 0.9150 0.9014 18.2963 62.6585 2.63479 69.66452 BL CG CW HL

5 0.9245 0.9087 16.0277 61.1132 2.53483 69.52037 BL HW CG CW SC

5 0.9229 0.9069 16.7205 61.7178 2.56050 70.12502 BL HW CG CW EL

6 0.9357 0.9190 12.9492 58.2642 2.38832 68.07263 BL HW CG CW EL SC

6 0.9347 0.9177 13.4159 58.7440 2.40749 68.55243 HW CG CW HL EL SC

7 0.9488 0.9325 9.0783 53.4648 2.18036 64.67434 BL HW CG CW HL EL SC

7 0.9375 0.9176 14.1679 59.4435 2.40882 70.65305 BC HW CG CW HL EL SC

8 0.9560 0.9393 7.8103 50.8840 2.06763 63.49478 BL HW CG CW PW HL EL SC

8 0.9492 0.9298 10.8875 55.2157 2.22242 67.82645 BL HW CG CW RL HL EL SC

9 0.9578 0.9388 9.0129 51.6514 2.07561 65.66342 BL HW CG CW RL PW HL EL SC

9 0.9562 0.9364 9.7409 52.7787 2.11498 66.79071 BC BL HW CG CW PW HL EL SC

10 0.9578 0.9356 11.0000 53.6311 2.12881 69.04428 BC BL HW CG CW RL PW HL EL SC

119

Appendix Table 8. Best models for Short-eared Somali does regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.6463 0.6435 37.7882 167.5895 1.91936 173.27783 CG

1 0.3565 0.3514 169.526 243.5944 2.58887 249.28281 BC

2 0.6976 0.6927 16.4898 149.7091 1.78200 158.24164 BC CG

2 0.6665 0.6611 30.6007 162.1171 1.87121 170.64962 HW CG

3 0.7209 0.7140 7.8975 141.5275 1.71893 152.90421 BC HW CG

3 0.7072 0.7000 14.1164 147.6037 1.76054 158.98048 BC CG EL

4 0.7274 0.7185 6.9201 140.5122 1.70559 154.73317 BC HW CG EL

4 0.7263 0.7174 7.4090 141.0123 1.70895 155.23319 BC HW CG PW

5 0.7317 0.7206 6.9862 140.5146 1.69921 157.57975 BC HW CG PW EL

5 0.7312 0.7200 7.2175 140.7552 1.70082 157.82027 BC HW CG RL EL

6 0.7359 0.7227 7.0533 140.4861 1.69270 160.39541 BC HW CG RL PW EL

6 0.7354 0.7221 7.2983 140.7450 1.69443 160.65432 BC HW CG CW PW EL

7 0.7403 0.7251 7.0356 140.3336 1.68545 163.08705 BC HW CG CW RL PW EL

7 0.7377 0.7223 8.2448 141.6280 1.69406 164.38145 BC HW CG CW RL PW HL

8 0.7425 0.7250 8.0749 141.2956 1.68568 166.89333 BC HW CG CW RL PW HL EL

8 0.7405 0.7229 8.9521 142.2437 1.69198 167.84138 BC BL HW CG CW RL PW EL

9 0.7426 0.7228 10.0000 143.2144 1.69232 171.65626 BC BL HW CG CW RL PW HL EL

Appendix Table 9. Best models for Short-eared Somali bucks regression equation

Model R2 Adj.

R2

C (p) AIC Root

MSE

SBC Variables in Model

1 0.6790 0.6650 19.857 55.1721 2.90122 57.60982 BC

1 0.6658 0.6513 21.525 56.1720 2.95983 58.60978 HW

2 0.8091 0.7918 5.2915 44.1728 2.28730 47.82945 BC HW

2 0.7811 0.7612 8.8582 47.5979 2.44948 51.25455 CG HL

3 0.8456 0.8235 2.6521 40.8743 2.10573 45.74976 BC BL HW

3 0.8360 0.8126 3.8722 42.3802 2.17012 47.25569 BC HW CW

4 0.8729 0.8475 1.1768 38.0092 1.95767 44.10360 BC BL HW CW

4 0.8646 0.8375 2.2337 39.5913 2.02061 45.68570 BC BL HW HL

5 0.8837 0.8531 1.8045 37.7930 1.92145 45.10628 BC BL HW CW HL

5 0.8753 0.8425 2.8707 39.5316 1.98943 46.84483 BC BL HW CW EL

6 0.8876 0.8501 3.3078 38.9399 1.94070 47.47201 BC BL HW CG CW HL

6 0.8845 0.8460 3.6963 39.6097 1.96687 48.14179 BC BL HW CW HL EL

7 0.8893 0.8438 5.0843 40.5462 1.98130 50.29716 BC BL HW CG CW PW HL

7 0.8890 0.8433 5.1278 40.6233 1.98436 50.37427 BC BL HW CG CW HL EL

8 0.8896 0.8344 7.0464 42.4789 2.03953 53.44874 BC BL HW CG CW PW HL SC

8 0.8896 0.8344 7.0506 42.4863 2.03984 53.45620 BC BL HW CG CW PW HL EL

9 0.8899 0.8238 9.0126 44.4187 2.10389 56.60744 BC BL HW CG CW RL PW HL SC

9 0.8897 0.8236 9.0328 44.4546 2.10540 56.64336 BC BL HW CG CW RL PW HL EL

10 0.8900 0.8114 11.000 46.3961 2.17675 59.80377 BC BL HW CG CW RL PW HL EL SC

120

Appendix Table 10. GLM analysis output of quantitative traits of does

Dependent

Variable

Source DF Type III SS Mean Square F Value Pr > F

BC Population 2 9.1938626 4.5969313 5.47 0.0045

Error 465 391.1138297 8411050

BW Population 2 6397.612637 3198.806318 139.91 <.0001

Error 465 10631.26967 22.86295

BL Population 2 2294.696848 1147.348424 80.49 <.0001

Error 465 6628.488515 14.254814

HW Population 2 3473.864495 1736.932248 181.42 <.0001

Error 465 4451.987535 9.574167

CG Population 2 3892.400282 1946.200141 141.00 <.0001

Error 465 6418.31553 13.80283

CW Population 2 207.4507228 103.7253614 34.93 <.0001

Error 465 1380.662525 2.969167

RL Population 2 121.7370070 60.8685035 67.34 <.0001

Error 465 420.2816896 0.9038316

PW Population 2 28.07400712 14.03700356 10.37 <.0001

Error 465 629.6327236 1.3540489

EL Population 2 602.7472956 301.3736478 271.33 <.0001

Error 465 934.267128 2.009177

HL Population 2 6238.980174 3119.490087 271.33 <.0001

Error 435 5001.25473 11.49714

121

Appendix Table 11. GLM analysis output of quantitative traits of bucks

Dependent

Variable

Source DF Type III SS Mean Square F Value Pr > F

BC Population 2 1.11480662 0.55740331 0.90 0.4076

Error 130 80.19346405 0.61687280

BW Population 2 3214.326027 1607.163013 41.69 <.0001

Error 130 5011.888410 38.552988

BL Population 2 2083.250170 1041.625085 53.28 <.0001

Error 130 2541.268627 19.548220

HW Population 2 3498.056324 1749.028162 85.14 <.0001

Error 130 2670.627887 20.543291

CG Population 2 2661.677478 1330.838739 46.16 <.0001

Error 130 3747.739815 28.828768

CW Population 2 125.7312956 62.8656478 11.84 <.0001

Error 130 690.3664488 5.3105111

RL Population 2 24.38291808 12.19145904 6.10 0.0029

Error 130 259.8464052 1.9988185

PW Population 2 41.98361754 20.99180877 6.65 0.0018

Error 130 410.2193900 3.1555338

EL Population 2 182.8583055 91.4291527 18.22 <.0001

Error 130 652.3898148 5.0183832

HL Population 2 809.4438450 404.7219225 17.47 <.0001

Error 87 2015.581155 23.167599

SC Population 2 48.53722091 24.26861046 4.35 0.0149

Error 130 725.6921024 5.5822469

122

Appendix Table 12. GLM analysis output of growth traits of Bati kids for the effect of sex, parity and

type of birth

Dependent

Variable

Source DF Type III SS Mean

Square

F

Value

Pr > F

Birth weight Parity 4 3.66487187 0.91621797 3.59 0.0082

Sex 1 1.74312236 1.74312236 6.84 0.0100

Birth type 1 1.60270690 1.60270690 6.29 0.0134

Error 129 32.88214839 0.25490038

30 days live

weight

Parity 4 10.92406356 2.73101589 2.63 0.0375

Sex 1 6.14358719 6.14358719 5.92 0.0164

Birth type 1 5.62436543 5.62436543 5.42 0.0216

Error 123 127.7033286 1.0382384

90 days live

weight

Parity 4 43.91982937 10.97995734 2.64 0.0379

Sex 1 28.90658721 28.90658721 6.94 0.0097

Birth type 1 19.72173615 19.72173615 4.73 0.0317

Error 109 454.1798064 4.1667872

180 days

live weight

Parity 4 11.61215631 2.90303908 0.51 0.7253

Sex 1 1.62948532 1.62948532 0.29 0.5923

Birth type 1 32.71796530 32.71796530 5.80 0.0179

Error 100 564.4437968 5.6444380

Birth-90

day’s daily

weight gain

Parity 4 5688.419665 1422.104916 3.05 0.0198

Sex 1 2090.647230 2090.647230 4.49 0.0363

Birth type 1 1284.271174 1284.271174 2.76 0.0996

Error 109 50742.87631 465.53098

91-180 days

daily weight

gain

Parity 4 3566.694120 891.673530 2.51 0.0466

Sex 1 282.162531 282.162531 0.79 0.3750

Birth type 1 32.770185 32.770185 0.09 0.7620

Error 98 34807.89031 355.18255

123

Appendix Table 13. GLM analysis output of growth traits of Borena kids for the effect of sex, parity

and type of birth

Dependent

Variable

Source DF Type III SS Mean Square F Value Pr > F

Birth weight Parity 4 4.84859784 1.21214946 4.12 0.0038

Sex 1 4.11716286 4.11716286 13.98 0.0003

Birth type 1 1.66216419 1.66216419 5.64 0.0192

Error 113 33.28568961 0.29456362

30 days live

weight

Parity 4 5.88410183 1.47102546 1.44 0.2272

Sex 1 10.39588084 10.39588084 10.15 0.0019

Birth type 1 5.37992190 5.37992190 5.25 0.0239

Error 104 106.5001708 1.0240401

90 days live

weight

Parity 4 22.62149798 5.65537449 2.13 0.0825

Sex 1 13.34547518 13.34547518 5.03 0.0271

Birth type 1 0.03842722 0.03842722 0.01 0.9044

Error 98 259.9372177 2.6524206

180 days

live weight

Parity 4 8.05571806 2.01392951 0.87 0.4841

Sex 1 14.96018835 14.96018835 6.48 0.0126

Birth type 1 2.76801755 2.76801755 1.20 0.2765

Error 91 210.2023415 2.3099158

Birth-90

day’s daily

weight gain

Parity 4 2849.631976 712.407994 2.07 0.0902

Sex 1 509.926278 509.926278 1.48 0.2261

Birth type 1 201.037511 201.037511 0.58 0.4462

Error 98 33683.65356 343.71075

91-180 days

daily weight

gain

Parity 4 2775.144564 693.786141 3.07 0.0202

Sex 1 180.131755 180.131755 0.80 0.3742

Birth type 1 426.630673 426.630673 1.89 0.1727

Error 91 20556.02961 225.89044

124

Appendix Table 14. GLM analysis output of growth traits of Short-Eared Somali kids for the

effect of sex, parity and type of birth

Dependent

Variable

Source DF Type III SS Mean

Square

F Value Pr > F

Birth weight Parity 4 1.31728430 0.32932108 3.05 0.0289

Sex 1 2.28866899 2.28866899 21.23 <.0001

Birth type 1 0.03442982 0.03442982 0.32 0.5755

Error 36 3.88159364 0.10782205

30 days live

weight

Parity 4 5.20793204 1.30198301 1.48 0.2278

Sex 1 8.25563195 8.25563195 9.41 0.0041

Birth type 1 1.45747742 1.45747742 1.66 0.2058

Error 35 30.69139258 0.87689693

90 days live

weight

Parity 4 15.87046078 3.96761519 2.49 0.0620

Sex 1 10.34736129 10.34736129 6.50 0.0156

Birth type 1 1.33629019 1.33629019 0.84 0.3663

Error 33 52.55551435 1.59259134

180 days live

weight

Parity 4 1.64578164 0.41144541 0.14 0.9674

Sex 1 13.62177598 13.62177598 4.52 0.0428

Birth type 1 2.34843341 2.34843341 0.78 0.3852

Error 27 81.3899194 3.0144415

Birth-90 day’s

daily weight

gain

Parity 4 1979.498940 494.874735 2.32 0.0776

Sex 1 367.345481 367.345481 1.72 0.1986

Birth type 1 241.443008 241.443008 1.13 0.2953

Error 33 7044.15882 213.45936

91-180 days

daily weight

gain

Parity 4 2217.084290 554.271072 3.37 0.0253

Sex 1 197.463395 197.463395 1.20 0.2840

Birth type 1 115.150973 115.150973 0.70 0.4110

Error 24 3946.841694 164.451737

125

Appendix B: Semi structured questionnaire used for indigenous goat survey

Name of enumerator_________________ Date: ______________________

Questionnaire number: ______________

Zone: _____________________________

District: _____________________ Kebele/Village____________________

Part 1. General information of households

1.1.Respondent's Sex: 1. Male 2. Female

1.2.Marital status of respondents a. Married b. Single c. Divorced

1.3.Respondent's Age (in years) ______

1.4.Respondent's Educational level 1. Illiterate (unable to read & write) 2. Reading and

writing 3. Adult education 4. Religious school, 5. Primary (1-8), 6.

Secondary (9-12) 7. Above secondary school

1.5.Household family size (number): Male ______ Female______ Total ______

1.6.What is your major farming activity? 1. Livestock production 2. Crop -livestock

production3. Other (Specify)_________________

1.7.Land holding (in ha)

Own Rented

a. Cropping land _________ ________

b. Fallow land _________ ________

c. Grazing _________ ________

d. Others (specify) _______________

1.8.Trend in land holding 1. Decreasing 2. Increasing 3. Stable

If decreasing why? ___________________________________________

1.9. Livestock ownership of households

1.10. Goat flock profile in number

a. Male kids < 6 months __________

b. Female kids < 6 months _________

c. Male 6 months to 1 year ________

d. Female 6 months to 1 year ______

e. Male > 1 year (Intact) _________

Species Number Trend in the last 10 years

Increasing Decreasing Constant Reason

Goat

Cattle

Sheep

Chicken

Camel

Donkey

Mule

Horse

Beehives

126

f. Female > 1 year _____________

g. Castrate _____________

1.11. Major crops grown

Main

rain

season

Short

rain

Irrigat

ed Main

rain

season

Short

rain

Irrigated

a. barley e. sorghum

b. wheat f. bean

c. teff g. pea

d. maize others

___________

1.12. Non-farm activities

1. Hand craft 2. Trading 3.Daily labor 4. Others (specify) _______________

1.13. Rank your farming and non-farm activities according to the respective criteria (1 for

the most important)

Household

staple diet

Household

Cash

income

a. Livestock production

b. Crop production

c. Hand craft

d. Trading

e Daily labor

f Others (_____________)

Part 2. Production and management systems

2.1. General

2.1.1. Production system

Mixed crop-livestock system

Agro-pastoralist

Pastoralist

Other (Specify)________________

2.1.2. Mobility pattern

Family Reason for movement Flock Reason for movement

Sedentary

Transhumance ____________________ _________________

Nomadic ____________________ _________________

2.1.3. Purpose of keeping goats (put in order of importance)

127

Purpose milk meat Wealth

status

ceremonies manure blood skin saving income gift

Rank

Others (specify) ______________________________________________________

2.1.4. If you use goats for milk production,

a. Average estimated milk production of doe per day (litters) during;

Wet season ____________Dry season____________

b. Lactation length (months) Maximum ___________minimum ________

2.1.5. Frequency of milking

Wet season Dry season

Once a day

Twice a day

Three times a day

2.1.6. Milk feeding up to weaning

1. Unrestricted suckling

2. Restricted suckling

2.1.7. Uses of goats milk

a. Market

b. household consumption c. others _________

2.1.8. If the family is making use of it, explain the way of preparation and utilization ____________________________________________________________________ ____________________________________________________________________

Average weaning age of kids in months: _____________________________

2.1.9.What type of mechanism you use to wean kids? _______________________

2.1.11. Members of household and hired labour responsible for goat activities

Family

Activities female male

≤15years >15years ≤15years >15years

Purchasing

Selling

Herding

Breeding

Caring sick animals

Feeding

Milking

Making dairy products

Selling dairy products

Barn cleaning

Slaughtering

128

2.2. Feeding and grazing management

1.2.1. Feed source (tick under each season and rank them)

Type of feed source Wet season Rank Dry season Rank

Natural pasture

Established pasture

Hay

Crop residues

Fallow land

Concentrate

Others

(Specify______________________________________________ 1.2.2. Crop residues used for goats’ feed (Rank according to priority)

Residues Wet season Dry season

Teff

Wheat

Barley

Sorghum

Maize

Bean

Pea

Lentil

Chick pea

Others (Specify) ______________________________________________

1.2.3. Grazing land ownership : 1. Privet 2. Communal 3. Both

1.2.4. Grazing and /or browsing method

Wet season Dry season

Free

Herded free grazing

Paddock

Tethered

Zero

Others (Specify______________________________________________

1.2.5. Length of grazing and/ or browsing time (in hours):

Wet season

a. Morning from_____to ______hours.

b. Afternoon _____to________hours.

c. Goats graze and or brows all the day

129

Dry season

a. Morning from_______to _____hours.

b. Afternoon _________to________ hours.

c. Goats graze and or brows all the day

1.2.6. Trend in communal grazing areas?

a. Decreasing b. Increasing C. Stable

What do you think the reason?

____________________________________________

1.2.7. How is goat flock herded during the day time?

a. Male and female are separated

b. Males and female are together

c. kids are separated

d. All classes goats herded together

1.2.8. Goat flock is herded

a. Together with cattle

b. Goats herded separately

c. Together with sheep

d. Together with camel

e. Together with calves

f. Together with equines

g. All herded together

1.2.9. Way of herding

a. Goats of a household run as a flock

b. Goats of more than one household run as a flock, if it is specify the number of

households mix their goats___________________________________

c. Others (specify) ___________________________________________

1.2.10. Is there seasonal fluctuation in feed supply? 1= Yes 2= No

2.2.11. At which month(s) of the year do you experience feed shortage?

______________________

2.2.12. Do you supplement your goats? 1= Yes 2= No

2.2.13. If your answer is yes, what is your supplementation system (Rank according to

importance)

Supplement type Wet season Dry season

Roughage

Minerals (salts)/vitamins

Concentrates

Others (specify)

2.2.14. Concentrates used for goats feeds( rank the most frequent used 1 and so on)

Type Rank

Homemade grain

Oil seed cakes

Local brewery by-products

Flour by-products

Others (Specify______________________________________________

130

2.2.15. Do you practice goat fattening ___________ 1= Yes 2=No

2.2.16. If your answer is yes for question no. 2.2.15, which categories of animals do you

fatten?

a. Older males

b. Older female

c. Castrates

d. Young males

e. Young female

f. Culled young male

g. Culled Young female

Name 3 categories of goats you use for fattening in order of importance

1.______________ 2. ___________________ 3._______________________

2.2.17. At which periods of the year do you commonly fatten goat?

Season fattening duration (months) Reasons

1. ____________ ______________ _______________________________

2. ____________ ______________ _______________________________

3. ____________ ______________ _______________________________

2.2.18. What type of feed resources you use to fatten goats?

a. Naturel Pasture

b. Crop residues

c. Concentrate

d. Others(specify) __________________

2.3. Watering

2.3.1. Source of water

Source Wet season Dry season Source Wet season Dry season

Water well Spring

Rain water Dam/pond

River Pipe water

Others (specify) ____________________

2.3.2. Distance to nearest watering point

Distance Wet season Dry season

Watered at home

<1km

1–5 km

6–10 km

>10 km

2.3.3. Are kids watered with the adults? _________ 1= Yes 2= No

If no, describe watering distance and frequency of kids_______________________

131

2.3.4. Frequency of watering

Frequency Wet season Dry season

Freely available

Once a day

Once in 2 days

Others_____________________________________________________

2.4. Housing

2.4.1. Housing/enclosure for adult goat (Tick one or more boxes)

With roof

a. In family house

b. Separate house

c. Veranda

Without roof a. Kraal

b. Yard

c. None

Others (specify)

2.4.2. Housing materials

Type Roof Wall Floor

a. Iron sheets

b. Grass/Bushes

c. Wood

d. Stone/bricks

e. Concrete

f. Earth/mud

Others ________

2.4.3. Are kids housed with adults?___________ 1= Yes 2=No

If no, specify_____________________________________

2.4.4. Are goats housed together with other animals? ________1= Yes 2= No.

2.5. Health management

2.5.1. What are the major goats diseases occur frequently in your area? List in order

of importance.

i. ____________________________________

Clinical signs__________________________________________________________

ii. ___________________________________

Clinical signs___________________________________________________________

iii. _____________________________________

Clinical sign____________________________________________________________

iv. ___________________________________

Clinical signs___________________________________________________________

v. ___________________________________

vi. Clinical signs___________________________________________________

2.5.2. Do you have access to veterinary services? 1. Yes 2. No

132

2.5.3. If yes, which type of veterinary service you accessed?

a. Government veterinarian

b. Private veterinarian

c. NGOs

d. CAHWs

2.5.4. Distance to nearest veterinary services

a. 1-5km

b. 6-10km

c. >10km

d. Other

e. (specify)_________

2.5.5. Most animals are provided with veterinary treatment when they are sick

a. Never, why? __________________________________________

b. occasionally

c. regularly

2.5.6. Most animals are subject to traditional treatments

a. Never, why? __________________________________________

b. Occasionally

c. Regularly

2.5.7. Adaptability traits of goats

Adaptability good moderate less

Disease

parasites

Heat

Frost

Drought

Feed shortage

Water shortage

2.6. Breeding practices

2.6.1. Do you have breeding buck?_________ 1= Yes 2= No

If yes,

a. Number local breeding buck? __________________

b. Number of crossbred breeding buck? ____________

2.6.2. If you have crossbred buck, is it a. Exotic b. Local?

If exotic, how do you have it? ______________________________

2.6.3. If you have more than one breeding buck, why do you need to keep more than one?

________________________________________________________

2.6.4. For how many years on the average is the one buck serving in your flock?

_________

2.6.5. Is there any special management for breeding buck? ________ 1= Yes 2= No

2.6.6. If yes, specify type of management________________________________

2.6.7. Source of breeding buck

133

a. Born in the flock

b. Purchased

c. Neighbours

d. Communal

e. Others(specify)____________

2.6.8.Purpose of keeping buck

a. Mating

b. Socio-cultural

c. Fattening

d. Other(specify)______________

2.6.9.Do you practice selection for?

a. Breeding male 1= Yes 2= No Breeding female 1= Yes 2= No

2.6.10. Which traits do you consider in selecting breeding buck and doe? Rank the traits in

order of importance for selection.

2.6.11. Age of selection (months); Breeding male _______, Breeding female _________

2.6.12. Age of 1stservice (month); Breeding male _________, Breeding female ________

2.6.13. Age at 1st kidding (month) _______________

2.6.14. Average number of kidding per doe life time ___________

2.6.15. Average kidding interval of doe (months) _____________

2.6.16. Type of mating used

a. Controlled

b. Uncontrolled (hand mating)

c. Uncontrolled (natural mating)

2.6.17. If uncontrolled, what is the reason?

a. Goats growth and/or browse together

b. Lack of awareness

c. Insufficient number of bucks

d. Others (specify) _________________

Traits to select doe Rank Traits to select buck Rank

Color Color

Body size/appearance Body size

Kid survival doubt Fertility

Paternal history Paternal history

Maternal history Maternal history

Age at first sexual maturity Libido

Kidding interval Growth rate

Litter size Adaptability

Milk yield Walk ability

Temperament Horn

Horn Others(specify) _____

Walk ability

Adaptability

Others(specify) __________

134

Could you be able to identify the sire of a kid? _______1= Yes 2= No

If yes, specify the criteria used to identify __________________

________________________________________________________

2.6.19. Do you allow your buck to serve does other than yours?

Reason

a. Yes ______________________________________________________

b. No ______________________________________________________

2.6.20. Do you allow your doe to be served by anyone else buck?

Reason

a. Yes _________________________________________

b. No __________________________________________

2.6.21. Kidding pattern, occurrence of most births(Tick one or more boxes then rank top

three )

2.6.22. Do you castrate your buck? 1= Yes 2= No

2.6.23. If you castrate your buck, what are your reasons for castration?

a. Control breeding

b. Improve fattening

c. Better price

d. Others ___________________

2.6.24. Specify Castration method you used.

a. By your own (traditional)

b. Veterinarians(modern)

2.6.25. If you castrate traditionally, explain the technique of castration? _____________

2.6.26. At what age do you castrate bucks? ____________________

2.7. Marketing

2.7.1.Which class of goat do you sell first in case of cash needed?

2.7.2. Average market age in month male_________ female__________

January July Top 3 months most births occur

February August 1. ____________________

March September 2. ____________________

April October 3. ____________________

May November

June December

Class Rank

Buck kids less than one year

Doe kids less than one year

Breeding does

Breeding bucks

Castrated

Old does

Old bucks

135

2.7.3. Average culling age due to old age male_________ female__________

2.8. Goat production constraints

2.8.1. What are the main constraints for goat production? (Rank with significance)

If yes mark(

)

Rank

a. Drought

b. Feed shortage

c.Water shortage

d.Disease

e. Predator

f. Market

g. Labor shortage

h. Lack of superior genotypes

I. Others (specify) _________

136

Appendix C: Goats physical description recording format and respective codes

Name of enumerator_______________________ Date: ______________

Zone: ___________________________________

District: _________________________Kebele/Village_______________

Goat type/breed: ________________________

No. Sex Body

condition

Coat color

pattern

Coat color Head

(facial)

profile

Horn

presence

Horn

shape

Horn

orientation

Ear

orientation

Back

profile

Wattles Ruff Beard

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Sex: F= Female M= Male, Coat color pattern: 1= plain 2= Patchy/pied 3= Spotted, Coat color: 1 = White, 2=dark red, 3 = Black, 4= Grey, 5 = light red, Head (facial) profile: 1 =

Straight, 2 = concave, 3= convex, Horn presence: 1= Present 2= Absent 3= Rudimentary, Horn shape:1= straight, 2= curved, 3= spiral, 4= corkscrew, Horn

orientation: 1= lateral(sideways), 2= obliquely upward, 3= back ward, Ear orientation: 1= erect, 2= pendulous, 3= semi-pendulous, 4= carried horizontally, Back

profile: 1= straight, 2= slopes up towards the rump, 3= slopes down from withers, 4=curved(dipped), Wattles: 1= Present 2= Absent, Ruff: 1= Present 2= Absent,

Beard:1= Present 2= Absent

137

Appendix D: Description of quantitative traits measured for each sample animal

Measurements Description

Body weight (BW) The live body weight taken using spring balance (in kilograms)

Body length (BL) The horizontal distance from the point of shoulder to the pin bone

to the nearest centimeter

Height at wither

(WH)

the (vertical) height (in centimeters) from the bottom of the front

foot to the highest point of the shoulder between the withers

Chest girth (CG) the circumference of the body (in centimeters) immediately behind

the shoulder blades in a vertical plane, perpendicular to the long

axis of the body

Chest width (CW) The width of the chest between the briskets to the nearest

centimeter

Rump length (RL) Distance from the most cranial and most dorsal point of the hip to

the most caudal point of the pin bone

Pelvic width (PW) The distance between the pelvic bones, across dorsum to the nearest

centimeter

Horn length (HL) From the base of the horn at the skull along the dorsal surface to the

tip of the horn using tape meters to the nearest centimeter

Ear length (EL) The length of the ear on its exterior side from its root at the poll to

the tip to the nearest centimeter

Scrotal

Circumference (SC)

Pushing the testicles to the bottom of the scrotum and the widest

Circumference measured to the nearest centimeter

138

Appendix E: Quantitative traits measurement recording format

No. BW BL HW CG CW RL PL HL EL SC

1

2

3

4

5

6

7

8

9

10

11

12

13

14

BW=Body weight, BL= Body Length, HW= Height at Withers, CG= Chest Girth, CW= Chest width, RL= Rump

Length, PW= Pelvic Width, HL= Horn Length, EL= Ear Length, LH= Length of Head and SC= Scrotum

Circumference

139

Appendix F: Descriptions of body condition score

Score Condition Features

1 Very thin Back bone prominent and sharp, ends of short ribs are sharp, easy to

press between, over and around

2 Thin Backbone prominent but smooth, short ribs are well rounded ends can

feel between, over and around smoothly

3 Average Backbone can be felt but smooth and rounded, short ribs ends are

smooth and well covered and felt with firm pressure

4 Fat Backbone detected with pressure on the thumb, individual short ribs

can be felt with firm pressure

5 Obese Back bone can be felt with firm pressure and hard to felt short ribs

even with firm pressure

140

Appendix G: Growth performance recording format

Owner’s name __________________________________Name of enumerator: ____________________

Zone: __________________ District: ________________ Kebele/Village ___________________

Dam’s Kid

Remarks

ID.

No.

Color Body

cond.

Dentition Parity Postpartum

wt.

Origin

(market

/born)

Id. Color Sex Type

of

birth

Birth

date

Birth

wt.

30 days

wt. (kg)

90 days

wt. (kg)

180 days wt.

(kg)

Date Wt.

Date Wt.

Date Wt.